Re: [R] sas vs r
On Wed, Apr 28, 2004 at 11:13:30AM +0200, Henric Nilsson wrote: At 05:24 2004-04-28, Liliana Forzani wrote: I have a code in sas (NLMIXED) and I have a hard time converting to r 1)it is poisson, with random intercept, but it have an offset. Means, I do not want one of the coefficient to be estimate. Means, may model is g(mean) = beta X + Z, Z fixed, X fixed and beta to be estimate I am using glmmML. If I recall correctly, neither glmmML nor glmmPQL (from MASS) handles offset terms. But GLMM in the lme4 package does. glmmML handles offset terms. I am pretty sure that glmmPQL does too. 2) the same but I have random slope (and I think with glmmML I can use only random intercept) GLMM in lme4 can do this. 3) I try to use nlme, is this equivalent to NLMIXED? No, nlme fits non-linear and linear mixed-effect models with Gaussian error terms. I hope this helps, Henric __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Göran Broströmtel: +46 90 786 5223 Department of Statistics fax: +46 90 786 6614 Umeå University http://www.stat.umu.se/egna/gb/ SE-90187 Umeå, Sweden e-mail: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Hsieh
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Re: [R] R hang-up using lm
Göran Broström [EMAIL PROTECTED] writes: set.seed(3) yy - rnorm(20) gg - rep(1:10, 2) y - tapply(yy, gg, median) x - 1:10 z - lm(y ~ x) # OK z - lm(x ~ y) # crashes R I had to try it too: No crashes on Win2000 pro (1.8.1) or Linux (1.9.0), but (in both cases): lm(y ~ x) Call: lm(formula = y ~ x) Coefficients: (Intercept)x -0.8783 0.1293 lm(x ~ y) Call: lm(formula = x ~ y) Coefficients: (Intercept) 5.5 i.e., only an intercept estimate in the second case! Surely something is wrong!? I just tried it on the 64-bit system and got Göran's result. However, repeating the lm(x~y) bit seems to have gotten itself stuck after the 3rd time (looks like a memory runaway problem, currently at 3.6GB and counting...). So perhaps those who couldn't reproduce should try it with replicate(100, lm(x~y)) or so. -- O__ Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] nlm
Hi, I am performing deviance minimization on a biological model of reproductive incompatibility due to symbiotic bacteria, I have up to 15 parameter estimates, but even with 8 parameters. Using simulated data, I observe my nlm procedure do not converge to minimum value, how can I improve and make sure it converges? thanks, Stéphane -- Stéphane Dupas IRD c/o CNRS Laboratoire Populations Génétique et Evolution 1 av de la Terrasse 91198 Gif sur Yvette + 33 1 69 82 37 04 http://www.cnrs-gif.fr/pge/index.html http://www.cnrs-gif.fr/pge/index.php?lang=en __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Extracting numbers from somewhere within strings
Hello everybody, I have a bunch of strings like this: IBM POWER4+ 1.9GHz IBM RS64-III 500MHz IBM RS64-IV 600 MHz IBM RS64 IV 750MHz Intel Itanium 2 Processor 6M 1.5GHz Intel Itanium2 1 Ghz Intel Itanium2 1.5GHz Intel MP 1.6GHz I want to extract the processor speed. I am using grep(MHz, tpc$cpu, ignore.case=T) grep(GHz, tpc$cpu, ignore.case=T) to extract the unit, because there are only these two. But how to extract the number before it? (I am using R 1.8.0) In Perl one would match a regexp such as /([0-9.]+) ?[MG][Hh][Zz]/ and then obtain the number as $1. But the capability of returning $1 is apparently not implemented in grep() or any other function I could find. How is it best done? Thanks in advance, Lutz Prof. Dr. Lutz Prechelt; [EMAIL PROTECTED] Institut fuer Informatik; Freie Universitaet Berlin Takustr. 9; 14195 Berlin; Germany +49 30 838 75115; http://www.inf.fu-berlin.de/inst/ag-se/ __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R hang-up using lm
Le 28 avr. 04, à 11:18, Göran Broström a écrit : lm(y ~ x) Call: lm(formula = y ~ x) Coefficients: (Intercept)x -0.8783 0.1293 lm(x ~ y) Call: lm(formula = x ~ y) Coefficients: (Intercept) 5.5 Same on RAqua 181, and the 2 show: z[] ... $model Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce array into a data.frame And calling first z - lm(x ~ y) gives Error: cannot allocate vector of size 3043328 Kb HTH. -- Jean-Pierre Müller SSP / BFSH2 / UNIL / CH - 1015 Lausanne Voice:+41 21 692 3116 / Fax:+41 21 692 3115 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] glmmPQL
when I tried the example in glmmPQL I got an error library(nlme) summary(glmmPQL(y ~ trt + I(week 2), random = ~ 1 | ID, family = binomial, data = bacteria)) iteration 1 iteration 2 iteration 3 iteration 4 iteration 5 iteration 6 Error: No slot of name reStruct for this object of class lme Error in logLik([EMAIL PROTECTED]) : Unable to find the argument object in selecting a method for function logLik __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Extracting numbers from somewhere within strings
Lutz Prechelt [EMAIL PROTECTED] writes: Hello everybody, I have a bunch of strings like this: IBM POWER4+ 1.9GHz IBM RS64-III 500MHz IBM RS64-IV 600 MHz IBM RS64 IV 750MHz Intel Itanium 2 Processor 6M 1.5GHz Intel Itanium2 1 Ghz Intel Itanium2 1.5GHz Intel MP 1.6GHz I want to extract the processor speed. I am using grep(MHz, tpc$cpu, ignore.case=T) grep(GHz, tpc$cpu, ignore.case=T) to extract the unit, because there are only these two. But how to extract the number before it? (I am using R 1.8.0) In Perl one would match a regexp such as /([0-9.]+) ?[MG][Hh][Zz]/ and then obtain the number as $1. But the capability of returning $1 is apparently not implemented in grep() or any other function I could find. How is it best done? Thanks in advance, gsub() has \1 etc. For instance gsub(^.* ([0-9\\.]+) *[MG][Hh]z$,\\1,x) [1] 1.9 500 600 750 1.5 1 1.5 1.6 (Not exactly trivial to get that right, but neither is it in Perl...) -- O__ Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] connection to libraries problem
Hello All, Although I have downloaded some libraries such as multivariate data analysis library (multiv) and ade4, their functions such as pca or reconst are not recognised. Should I install any thing else or use any instruction so that R could find the location of libraries? Thanks for your quick response, Haleh Yasrebi __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R hang-up using lm
On 28 Apr 2004, Peter Dalgaard wrote:
Göran Broström [EMAIL PROTECTED] writes:
set.seed(3)
yy - rnorm(20)
gg - rep(1:10, 2)
y - tapply(yy, gg, median)
x - 1:10
z - lm(y ~ x) # OK
z - lm(x ~ y) # crashes R
I had to try it too: No crashes on Win2000 pro (1.8.1) or Linux (1.9.0),
but (in both cases):
lm(y ~ x)
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept)x
-0.8783 0.1293
lm(x ~ y)
Call:
lm(formula = x ~ y)
Coefficients:
(Intercept)
5.5
i.e., only an intercept estimate in the second case! Surely something is
wrong!?
I just tried it on the 64-bit system and got Göran's result. However,
repeating the lm(x~y) bit seems to have gotten itself stuck after the
3rd time (looks like a memory runaway problem, currently at 3.6GB and
counting...). So perhaps those who couldn't reproduce should try it with
replicate(100, lm(x~y)) or so.
RHEL 3, R 1.9.0 seg.faults:
set.seed(3)
yy - rnorm(20)
gg - rep(1:10, 2)
y - tapply(yy, gg, median)
x - 1:10
z - lm(y ~ x) # OK
str(y)
num [, 1:10] -0.853 -0.712 -0.229 -0.450 0.174 ...
- attr(*, dimnames)=List of 1
..$ : chr [1:10] 1 2 3 4 ...
dim(y)
[1] 10
z - lm(x ~ y)
replicate(100, lm(x~y))
Error in model.matrix.default(mt, mf, contrasts) :
invalid type for dimname (must be a vector)
lm(x~y)
Program received signal SIGSEGV, Segmentation fault.
Rf_getAttrib (vec=0x8f71200, name=0x81f47d8) at attrib.c:99
99 if (TAG(s) == name) {
(gdb) bt
#0 Rf_getAttrib (vec=0x8f71200, name=0x81f47d8) at attrib.c:99
#1 0x08122363 in Rf_isArray (s=0x8f71200) at util.c:413
#2 0x08069aef in Rf_dimnamesgets (vec=0x8f71200, val=0x8f627c8)
at attrib.c:581
#3 0x080cb845 in do_modelmatrix (call=0x8674200, op=0x8212f00, args=0x0,
rho=0x8f5eaf8) at model.c:1904
#4 0x080cc6dc in do_internal (call=0x4320, op=0x8204a78, args=0x8f710e8,
env=0x8f5eaf8) at names.c:1057
#5 0x080a74d2 in Rf_eval (e=0x86740b0, rho=0x8f5eaf8) at eval.c:375
#6 0x080a905b in do_set (call=0x8674040, op=0x82038c4, args=0x867405c,
rho=0x8f5eaf8) at eval.c:1271
#7 0x080a74d2 in Rf_eval (e=0x8674040, rho=0x8f5eaf8) at eval.c:375
#8 0x080a88ce in do_begin (call=0x867a068, op=0x82037c8, args=0x8674008,
rho=0x8f5eaf8) at eval.c:1046
#9 0x080a74d2 in Rf_eval (e=0x867a068, rho=0x8f5eaf8) at eval.c:375
#10 0x080a7779 in Rf_applyClosure (call=0x8f5ec80, op=0x867aaf4,
arglist=0x8f5ee5c, rho=0x8f5ed60, suppliedenv=0x8f5ecb8) at eval.c:566
#11 0x080cc9af in applyMethod (call=0x8f5ec80, op=0x867aaf4,
args=0x8f5ee5c,
rho=0x8f5ed60, newrho=0x8f5ecb8) at objects.c:119
#12 0x080cd01c in Rf_usemethod (generic=0x87aaf88 model.matrix,
obj=0x8f5a18c, call=0x867aa14, args=0x81f4998, rho=0x8f5ed60,
callrho=0x8f3ab40, defrho=0x8b2a974, ans=0xbfffd288) at objects.c:326
#13 0x080cd4b5 in do_usemethod (call=0x867aa14, op=0x8212308,
args=0x867aa30, env=0x8f5ed60) at objects.c:389
#14 0x080a74d2 in Rf_eval (e=0x867aa14, rho=0x8f5ed60) at eval.c:375
#15 0x080a7779 in Rf_applyClosure (call=0x875c02c, op=0x867a838,
arglist=0x8f5ee5c, rho=0x8f3ab40, suppliedenv=0x81f4998) at eval.c:566
#16 0x080a72f5 in Rf_eval (e=0x875c02c, rho=0x8f3ab40) at eval.c:410
#17 0x080a905b in do_set (call=0x875be6c, op=0x82038c4, args=0x875bfd8,
rho=0x8f3ab40) at eval.c:1271
#18 0x080a74d2 in Rf_eval (e=0x875be6c, rho=0x8f3ab40) at eval.c:375
#19 0x080a88ce in do_begin (call=0x875d598, op=0x82037c8, args=0x875be50,
rho=0x8f3ab40) at eval.c:1046
#20 0x080a74d2 in Rf_eval (e=0x875d598, rho=0x8f3ab40) at eval.c:375
#21 0x080a74d2 in Rf_eval (e=0x875da20, rho=0x8f3ab40) at eval.c:375
#22 0x080a88ce in do_begin (call=0x8760a88, op=0x82037c8, args=0x875da04,
rho=0x8f3ab40) at eval.c:1046
#23 0x080a74d2 in Rf_eval (e=0x8760a88, rho=0x8f3ab40) at eval.c:375
#24 0x080a7779 in Rf_applyClosure (call=0x8f3ad38, op=0x8760804,
arglist=0x8f3ace4, rho=0x821546c, suppliedenv=0x81f4998) at eval.c:566
#25 0x080a72f5 in Rf_eval (e=0x8f3ad38, rho=0x821546c) at eval.c:410
#26 0x080c0eda in Rf_ReplIteration (rho=0x821546c, savestack=136268184,
browselevel=0, state=0xbfffdeb0) at main.c:250
#27 0x080c1083 in R_ReplConsole (rho=0x821546c, savestack=0,
browselevel=0) at main.c:298
#28 0x080c190f in run_Rmainloop () at main.c:653
#29 0x0812480c in main (ac=1, av=0xbfffe3c4) at system.c:99
(gdb)
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
e-mail: [EMAIL PROTECTED]
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Re: [R] glmmPQL
I thinks I understand the porblem, you can not use glmmPQL if you have open lme4 On Wed, 28 Apr 2004, Liliana Forzani wrote: when I tried the example in glmmPQL I got an error library(nlme) summary(glmmPQL(y ~ trt + I(week 2), random = ~ 1 | ID, family = binomial, data = bacteria)) iteration 1 iteration 2 iteration 3 iteration 4 iteration 5 iteration 6 Error: No slot of name reStruct for this object of class lme Error in logLik([EMAIL PROTECTED]) : Unable to find the argument object in selecting a method for function logLik __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Emacs Speaks Statistics version 5.2.0 has been released
Emacs Speaks Statistics (ESS) version 5.2 is available for download at: http://www.analytics.washington.edu/downloads/ess/ess-5.2.0.tar.gz or http://www.analytics.washington.edu/downloads/ess/ess-5.2.0.zip Changes since 5.1.24 are listed below. Thanks, The ESS Core Team. Changes/New Features in 5.2.0: * ESS[BUGS]: new info documentation! now supports interactive processing thanks to Aki Vehtari (mailto:[EMAIL PROTECTED]); new architecture-independent unix support as well as support for BUGS v. 0.5 * ESS[SAS]: convert .log to .sas with ess-sas-transcript; info documentation improved; Local Variable bug fixes; SAS/IML statements/functions now highlighted; files edited remotely by ange-ftp/EFS/tramp are recognized and pressing SUBMIT opens a buffer on the remote host via the local variable ess-sas-shell-buffer-remote-init which defaults to ssh; changed the definition of the variable ess-sas-edit-keys-toggle to boolean rather than 0/1; added the function ess-electric-run-semicolon which automatically reverse indents lines containing only run;; C-F1 creates MS RTF portrait from the current buffer; C-F2 creates MS RTF landscape from the current buffer; C-F9 opens a SAS DATASET with PROC INSIGHT rather than PROC FSVIEW; C-F10 kills all buffers associated with .sas program; inferior aliases for SAS batch: C-c C-r for submit region, C-c C-b for submit buffer, C-c C-x for goto .log; C-c C-y for goto .lst * ESS[S]: Pressing underscore (_) once inserts - (as before); pressing underscore twice inserts a literal underscore. To stop this smart behaviour, add (ess-smart-underscore nil) to your .emacs after ess-site has been loaded; ess-dump-filename-template-proto (new name!) now can be customized successfully (for S language dialects); Support for Imenu has been improved; set ess-imenu-use-S to non-nil to get an Imenu-S item on your menubar; ess-help: Now using nice underlines (instead of `nuke-* ^H_') * ESS[R]: After (require 'essa-r), M-x ess-r-var allows to load numbers from any Emacs buffer into an existing *R* process; M-x ess-rdired gives a directory editor of R objects; fixed ess-retr-lastvalue-command, i.e. .Last.value bug (thanks to David Brahm) * ESS: Support for creating new window frames has been added to ESS. Inferior ESS processes can be created in dedicated frames by setting inferior-ess-own-frame to t. ESS help buffers can also open in new frames; see the documentation for ess-help-own-frame for details. (Thanks to Kevin Rodgers for contributing code.) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R hang-up using lm
On Wed, Apr 28, 2004 at 11:18:38AM +0200, Göran Broström wrote: On Wed, Apr 28, 2004 at 11:46:51AM +0300, Renaud Lancelot wrote: Martin Maechler a écrit : kjetil == kjetil [EMAIL PROTECTED] on Tue, 27 Apr 2004 19:19:59 -0400 writes: kjetil On 27 Apr 2004 at 16:46, Raubertas, Richard wrote: Within the last few weeks, someone else reported a similar problem when using the results of tapply in a call to rlm(). Note that the result of tapply is a 1D array, and it appears there is a general problem with using such a thing on the RHS in formula-based modeling functions: set.seed(3) yy - rnorm(20) gg - rep(1:10, 2) y - tapply(yy, gg, median) x - 1:10 z - lm(y ~ x) # OK z - lm(x ~ y) # crashes R (R 1.8.1 on Windows XP Pro) kjetil What exactly do you mean by crashes R kjetil Doing this in R1.9.0, windows XP pro, there is no indication of kjetil problems. nor is there with 1.9.0 or R-patched on Linux, nor with R 1.8.1 on Linux. no warning, no error, no problem at all. Is it really the above (reproducible, thank you!) example that crashes your R 1.8.1 ? It does it for me: Windows XP Pro, R 1.9.0 (P IV, 2.4 GHz, 256 Mo RAM). It freezes RGui and a few seconds later, a Windows message appears saying that Rgui front-end met a problem and must be closed. I had to try it too: No crashes on Win2000 pro (1.8.1) or Linux (1.9.0), but (in both cases): lm(y ~ x) Call: lm(formula = y ~ x) Coefficients: (Intercept)x -0.8783 0.1293 lm(x ~ y) Call: lm(formula = x ~ y) Coefficients: (Intercept) 5.5 i.e., only an intercept estimate in the second case! Surely something is wrong!? Obviousy, y, generated as above, has an attribute that confuses 'lm', because lm(x ~ as.vector(y)) works as expected. To add further to confusion, R-1.8.1 (Windows): glm(x ~ y) Error in model.matrix.default(mt, mf, contrasts) : invalid type for dimname (must be a vector) while 1.9.0 (Linux): glm(x ~ y) Call: glm(formula = x ~ y) Coefficients: (Intercept) 5.5 Degrees of Freedom: 9 Total (i.e. Null); 9 Residual Null Deviance: 82.5 Residual Deviance: 82.5 AIC: 53.48 Göran Best, Renaud -- Dr Renaud Lancelot vétérinaire épidémiologiste Ambassade de France - SCAC BP 834 Antananarivo 101 Madagascar tél. +261 (0)32 04 824 55 (cell) +261 (0)20 22 494 37 (home) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Göran Broströmtel: +46 90 786 5223 Department of Statistics fax: +46 90 786 6614 Umeå University http://www.stat.umu.se/egna/gb/ SE-90187 Umeå, Sweden e-mail: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Göran Broströmtel: +46 90 786 5223 Department of Statistics fax: +46 90 786 6614 Umeå University http://www.stat.umu.se/egna/gb/ SE-90187 Umeå, Sweden e-mail: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] connection to libraries problem
On 28 Apr 2004 at 11:08, haleh.yasrebi wrote: Hello All, Although I have downloaded some libraries such as multivariate data analysis library (multiv) and ade4, their functions such as pca or Hi library(packagename) after you start R session see ?library Cheers Petr reconst are not recognised. Should I install any thing else or use any instruction so that R could find the location of libraries? Thanks for your quick response, Haleh Yasrebi __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Petr Pikal [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Solving linear equations
lm.fit(A, b)$coefficients seems to do what I want, but, as you have rightly pointed out, the deviations most probably will not have constant variance (but should be normally distributed). Basically, I make measurements from which I obtain the vector b with variance in each of the values v. How would I fit my data then? (A is known and fixed). What's the best book to look at for solving those problems? Thanks, Tomek How do you wish to decide how to resolve the likely inconsistencies in the overdetermined system? If you assume the vertical deviations from a linear fit are normally distributed with constant variance, then quot;lmquot; should do what you want. _ It's fast, it's easy and it's free. Get MSN Messenger today! __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] nnet question
Please read the documentation: why is a logistic output equation appropriate for example. The iris3 example does not use the same arguments as you have, so you are claiming to know what you are doiung here. You *have* worked though the examples in the book this software supports, haven't you? On Mon, 26 Apr 2004, Erik Johnson wrote: I am using R 1.8.0, and am attempting to fit a Neural Network model of a time series (here called Metrics.data). It consists of one time series variable run on its lag (AR(1)). Basically, in an OLS model it would look like Metrics.data$ewindx ~ Metrics.data$ewindx.lag1 However, I am trying to run this through a neural network estimation. So far, I have been getting convergence very quickly, and do not believe it too be true. Here is the code and output. Please note that I am using all of the values for training and testing in one matrix, as I do not care about the testing results right now, I only want to capture weights. Here is the code and output nnet(metrics.data$ewindxlag1,metrics.data$ewindx,size=2, entropy=FALSE) # weights: 7 initial value 78858370643.085342 final value 78841786515.212158 converged a 1-2-1 network with 7 weights options were - When I run the iris3 example, the convergence looks much nicer (consisting of more than one iteration). Am I missing some fundamental understanding of this example? Thanks for any input. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] connection to libraries problem
haleh == haleh yasrebi [EMAIL PROTECTED] on Wed, 28 Apr 2004 11:08:00 +0100 writes: haleh Hello All, Although I have downloaded some libraries haleh such as multivariate data analysis library (multiv) haleh and ade4, their functions such as pca or reconst are haleh not recognised. Should I install any thing else or haleh use any instruction so that R could find the location haleh of libraries? Petr has already helped you, so, , === please, Please, PLEASE, PLEASE, P_L_E_A_S_E , P L E A S E === These are NOT 'libraries' but PACKAGES !!! The packages are put into one or more libraries full of packages, which you see when typing library(). The first argument of the function library() is called package phew..., thanks! Martin __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] p-values
The Bayesian framework is surely a good framework for thinking about inference, and for exploring common misinterpretations of p-values. P-values are surely unhelpful and to be avoided in cases where there is `strong' prior evidence. I will couch the discussion that follows in terms of confidence intervals, which makes the discussion simpler, rather than in terms of p-values. The prior evidence is in my sense strong if it leads to a Bayesian credible interval that is very substantially different from the frequentist confidence interval (though I prefer the term `coverage interval'). Typically the intervals will be similar if a diffuse prior is used, i.e., all values over a wide enough range are, on some suitable scale, a-priori equally likely. This is, in my view, the message that you should take from your reading. Examples of non-diffuse priors are what Berger focuses on. Consider for example his discussion of one of Jeffreys' analyses, where Jeffreys puts 50% of the probability on on a point value of a a continuous parameter, i.e., there is a large spike in the prior at that point. Berger commonly has scant commentary on the specific features of his priors that make the Bayesian results seem very different (at least to the extent of having a different feel) from the frequentist results. His paper in vol 18, no 1 of Statistical Science (pp.1-32; pp.12-27 are comment from other) seems more judicious in this respect than some of his earlier papers. It is interesting to speculate how R's model fitting routines might be tuned to allow a Bayesian interpretation. What family or families of priors would be on offer, and/or used by default? What default mechanisms would be suitable useful for indicating the sensitivity of results to the choice of prior? John Maindonald. From: Greg Tarpinian [EMAIL PROTECTED] Date: 28 April 2004 6:32:06 AM To: [EMAIL PROTECTED] Subject: [R] p-values I apologize if this question is not completely appropriate for this list. I have been using SAS for a while and am now in the process of learning some C and R as a part of my graduate studies. All of the statistical packages I have used generally yield p-values as a default output to standard procedures. This week I have been reading Testing Precise Hypotheses by J.O. Berger Mohan Delampady, Statistical Science, Vol. 2, No. 3, 317-355 and Bayesian Analysis: A Look at Today and Thoughts of Tomorrow by J.O. Berger, JASA, Vol. 95, No. 452, p. 1269 - 1276, both as supplements to my Math Stat. course. It appears, based on these articles, that p-values are more or less useless. If this is indeed the case, then why is a p-value typically given as a default output? For example, I know that PROC MIXED and lme( ) both yield p-values for fixed effects terms. The theory I am learning does not seem to match what is commonly available in the software, and I am just wondering why. Thanks, Greg John Maindonald email: [EMAIL PROTECTED] phone : +61 2 (6125)3473fax : +61 2(6125)5549 Centre for Bioinformation Science, Room 1194, John Dedman Mathematical Sciences Building (Building 27) Australian National University, Canberra ACT 0200. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] reading a sparse matrix into R
Have you considered the read.matrix.csr() function in pkg. e1071? It uses another sparse input format, but perhaps you can easily transform your data in the supported one. Also, in my experience, data frames are not the best basis for a sparse format since they might turn out to be very memory consuming and slow... The sparse formats provided by the SparseM package are better suited for this. -d Date: Tue, 27 Apr 2004 17:10:09 -0400 From: Aaron J. Mackey [EMAIL PROTECTED] Subject: [R] reading a sparse matrix into R To: [EMAIL PROTECTED] Message-ID: [EMAIL PROTECTED] Content-Type: text/plain; charset=US-ASCII; format=flowed I have a 47k x 47k adjacency matrix that is very sparse (at most 30 entries per row); my textual representation therefore is simply an adjacency list of connections between nodes for each row, e.g. nodeconnections A B C D E B A C D C A E D A E A F F E G H I'd like to import this into a dataframe of node/connection (character/vector-of-characters) pairs. I've experimented with scan, but haven't been able to coax it to work. I can also hack it with strsplit() myself, but I thought there might be a more elegant way. Thanks, -Aaron __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] (no subject)
From [EMAIL PROTECTED] Hi there. Is it possible to send wordtext to R and then code it your self? Can I by coding see if some results are correlated with others? Ex. If there is a low score in one collum and high in an other -if thats correlated? Bedst regards Lene [[alternative HTML version deleted]] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] helps on levelplot
On Wednesday 28 April 2004 01:35, Yan Wang wrote:
Thank you for the hints! I have some followup questions.
About the panel function, here is the code I copied from the example:
xyplot(NOx ~ C | EE, data = ethanol,
prepanel = function(x, y) prepanel.loess(x, y, span =
1), xlab = Compression Ratio, ylab = NOx (micrograms/J), panel =
function(x, y) {
panel.grid(h=-1, v= 2)
panel.xyplot(x, y)
panel.loess(x,y, span=1)
},
aspect = xy)
My question is what is the relation between the xyplot function and
panel.xyplot(x,y). In my case, I found that in the panel function, if
I only have panel.abline(), the levelplot wouldn't be drawn at all.
But I don't know how to specify the arguments in panel.levelplot(),
which is exactly the part that you used ... in your last reply. For
all sorts of possible ways I tried, I got various of errors.
I believe this is described in some detail in the documentation. Have
you read the entry for 'panel' in help(xyplot) ?
Generally speaking, each lattice function has its own panel function --
e.g. panel.xyplot, panel.levelplot, etc. The arguments they accept may
be different, and are described in their respective help pages.
Naturally, any high level function (like xyplot and levelplot) will
pass to its panel function enough information for the default panel
functions to work. Another way to find out what arguments are passed
would be to use
panel = function(...) print(names(list(...)))
BTW, I would recommend always using a ... argument in your panel
function definition.
I don't know if this answers your questions. If it doesn't please be
more specific in describing where your confusion lies.
About the label size for the colorkey, when I coded as you suggested:
levelplot(z~x*y, grid,at=seq(0,1,by=0.1),scales=list(cex=2),
colorkey=list(labels=list(cex=2, at=seq(0,1,by=0.1
I got error Error in draw.colorkey(x$colorkey) : invalid type/length
(3/1) in vector allocation. In fact, for whatever at I specified
in labels, I got the same error message.
Works for me as expected. Perhaps you are not using the latest R
(1.9.0).
Deepayan
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Re: [R] loading into a list
Delayed response (!)
But perhaps more transparent than
mget(ls(e), envir = e)
is simply
as.list(e)
-roger
Roger D. Peng wrote:
Or maybe
loadIntoList - function(filename) {
e - new.env()
load(filename, envir = e)
mget(ls(e), envir = e)
}
-roger
Achim Zeileis wrote:
On Tue, 20 Apr 2004 15:39:07 +0200 Tamas Papp wrote:
I have the following problem.
Use the same algorithm (with different parameters) to generate
simulation results. I store these in variables, eg A, B, C, which I
save into a file with
save(A, B, C, file=solution001.Rdata)
I do this many times. Then I would like to load the above, but in
such a manner that A, B, C woule be part of a list, eg
sol001 - loadIntoList(solution001.Rdata)
so that sol001 is a list with elements A, B, C.
I am looking for a way to implement the above function.
If your objects are always called A, B, and C, the following should
work:
loadIntoList - function(file) {
load(file)
return(list(A = A, B = B, C = C))
}
hth,
Z
The variables
are very large and I need a lot of time to compute them, so saving
loading the results is the only viable alternative.
Thanks,
Tamas
--
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E-mail: [EMAIL PROTECTED]
Please try to send only (latin-2) plain text, not HTML or other
garbage.
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Re: [R] Rtemp directories accumulating over time
On Tue, 27 Apr 2004 [EMAIL PROTECTED] wrote: There is a nuisance that the number of directories with name starting Rtmp (and always empty) in my temp directory is increasing over time. I put the following in my .Rprofile: tmp0001 - tempdir() setHook( packageEvent(base,onUnload), function(...) unlink( tmp0001, recursive=TRUE) ) which solves part of the problem, but not all. I don't see why: package base is never unloaded so that hook function is never run. (Indeed, no package/namespace is unloaded except by explicit user action, in particular not when R is terminated.) So there are also other tmpdirs made by R. Why, where, and why are they not removed at exit (when their content are removed)? They are removed by R. This is a Windows-only bug, as Windows sometimes does not act on commands to remove empty directories (but only sometimes). Session temporary directories should only be left around when a session crashes. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Problem with W2000
Have your ever had problem with Windows 2000 on supporting R 1.9.0? After the installation of R 1.9.0, when we ran it for the first time, the computer stopped and we had to reset the machine. Do you have any suggestions? Thanks Cristian = Cristian Pattaro = Unit of Epidemiology Medical Statistics Department of Medicines and Public Health University of Verona [EMAIL PROTECTED] = [[alternative HTML version deleted]] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Fedora 1 RPM Packages
I think this is appropriate for most users: if you want to use
--enable-R-shlib you can and probably should compile R yourself. (After
all, you are going to need the development tools for almost all uses of
libR.so.) It is not a zero-cost option: it does for example cause shared
objects in packages to be linked against libR.so not R.bin and so
increases considerably the run-time footprint.
On Tue, 27 Apr 2004, Ian Wallace wrote:
Don't know if this is the correct place to post this question however I
thought I would start here. The Fedora 1 packages are built without the
option '--enable-R-shlib' turned on in the R.spec file. Other software,
like, plr (the postgresql library that calls R) needs the shared lib.
Any chance that we can change the R.spec file to include:
[EMAIL PROTECTED] SPECS]$ diff -bu R.spec R.spec.orig
--- R.spec 2004-04-27 15:31:51.0 -0600
+++ R.spec.orig 2004-04-27 15:31:39.0 -0600
@@ -36,7 +36,6 @@
%build
export R_BROWSER=/usr/bin/mozilla
( %configure \
---enable-R-shlib \
--with-tcl-config=%{_libdir}/tclConfig.sh \
--with-tk-config=%{_libdir}/tkConfig.sh ) \
| egrep '^R is now|^ |^$' - CAPABILITIES
I'm not sure if there are other issues with using the shared library,
I'm very new to R and just joined the mailing list.
Thanks!
ian
--
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Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
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[R] numericDeriv
Dear All, I am trying to solve a Generalized Method of Moments problem which necessitate the gradient of moments computation to get the standard errors of estimates. I know optim does not output the gradient, but I can use numericDeriv to get that. My question is: is this the best function to do this? Thank you Jean, __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] reading a sparse matrix into R
David Meyer [EMAIL PROTECTED] writes: Have you considered the read.matrix.csr() function in pkg. e1071? It uses another sparse input format, but perhaps you can easily transform your data in the supported one. Also, in my experience, data frames are not the best basis for a sparse format since they might turn out to be very memory consuming and slow... The sparse formats provided by the SparseM package are better suited for this. The Matrix package (versions 0.8-1 and later) has a C function that does the opposite operation, converting a symmetric sparse matrix to a graph. I would look at the way that the graph is stored there (the formulation is from the Metis package of C code) and try to convert your adjacency graph to that formulation first. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
model.matrix (Re: [R] R hang-up using lm)
On Wed, Apr 28, 2004 at 12:59:54PM +0200, Göran Broström wrote: On Wed, Apr 28, 2004 at 11:18:38AM +0200, Göran Broström wrote: On Wed, Apr 28, 2004 at 11:46:51AM +0300, Renaud Lancelot wrote: Martin Maechler a écrit : kjetil == kjetil [EMAIL PROTECTED] on Tue, 27 Apr 2004 19:19:59 -0400 writes: kjetil On 27 Apr 2004 at 16:46, Raubertas, Richard wrote: Within the last few weeks, someone else reported a similar problem when using the results of tapply in a call to rlm(). Note that the result of tapply is a 1D array, and it appears there is a general problem with using such a thing on the RHS in formula-based modeling functions: set.seed(3) yy - rnorm(20) gg - rep(1:10, 2) y - tapply(yy, gg, median) x - 1:10 z - lm(y ~ x) # OK z - lm(x ~ y) # crashes R (R 1.8.1 on Windows XP Pro) kjetil What exactly do you mean by crashes R kjetil Doing this in R1.9.0, windows XP pro, there is no indication of kjetil problems. nor is there with 1.9.0 or R-patched on Linux, nor with R 1.8.1 on Linux. no warning, no error, no problem at all. Is it really the above (reproducible, thank you!) example that crashes your R 1.8.1 ? It does it for me: Windows XP Pro, R 1.9.0 (P IV, 2.4 GHz, 256 Mo RAM). It freezes RGui and a few seconds later, a Windows message appears saying that Rgui front-end met a problem and must be closed. I had to try it too: No crashes on Win2000 pro (1.8.1) or Linux (1.9.0), but (in both cases): lm(y ~ x) Call: lm(formula = y ~ x) Coefficients: (Intercept)x -0.8783 0.1293 lm(x ~ y) Call: lm(formula = x ~ y) Coefficients: (Intercept) 5.5 i.e., only an intercept estimate in the second case! Surely something is wrong!? Obviousy, y, generated as above, has an attribute that confuses 'lm', because lm(x ~ as.vector(y)) works as expected. To add further to confusion, R-1.8.1 (Windows): glm(x ~ y) Error in model.matrix.default(mt, mf, contrasts) : invalid type for dimname (must be a vector) so, model.matrix(x ~ y) (Intercept) 11 21 31 41 51 61 71 81 91 10 1 attr(,assign) [1] 0 but model.matrix(x ~ as.vector(y)) (Intercept) as.vector(y) 11 -0.853357506 21 -0.711872147 31 -0.228785137 41 -0.449739758 51 0.173914266 61 -0.138766243 71 -0.433799800 81 0.234183701 91 0.002728104 10 1 0.733590165 attr(,assign) [1] 0 1 AND rr - model.matrix.default(x ~ y) Segmenteringsfel [EMAIL PROTECTED]:~$ After a restart and repeating model.matrix.default(x ~ y) several times, I FINALLY got model.matrix.default(x ~ y) (Intercept) 11 21 31 41 51 61 71 81 91 10 1 attr(,assign) [1] 0 model.matrix.default(x ~ y) (Intercept)y 11 -0.853357506 21 -0.711872147 31 -0.228785137 41 -0.449739758 51 0.173914266 61 -0.138766243 71 -0.433799800 81 0.234183701 91 0.002728104 10 1 0.733590165 attr(,assign) [1] 0 1 model.matrix.default(x ~ y) Segmenteringsfel [EMAIL PROTECTED]:~$ (Don't ask me what's going on: but 'Segmenteringsfel' means 'Segmentation fault':) BTW, this was on Debian testing/unstable; R-1.9.0 -- Göran Broströmtel: +46 90 786 5223 Department of Statistics fax: +46 90 786 6614 Umeå University http://www.stat.umu.se/egna/gb/ SE-90187 Umeå, Sweden e-mail: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] reading a sparse matrix into R
I've used lists (generic vectors) for this, with integer storage mode. Then I can easily manipulate them in R, they don't take too much room, and C code to traverse them (e.g. find connected components) is fast. Did you have a need for a data frame? That seems like it might be painful to manipulate. I read the text file with readLines. Reid Huntsinger -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Aaron J. Mackey Sent: Tuesday, April 27, 2004 5:10 PM To: [EMAIL PROTECTED] Subject: [R] reading a sparse matrix into R I have a 47k x 47k adjacency matrix that is very sparse (at most 30 entries per row); my textual representation therefore is simply an adjacency list of connections between nodes for each row, e.g. nodeconnections A B C D E B A C D C A E D A E A F F E G H I'd like to import this into a dataframe of node/connection (character/vector-of-characters) pairs. I've experimented with scan, but haven't been able to coax it to work. I can also hack it with strsplit() myself, but I thought there might be a more elegant way. Thanks, -Aaron __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: model.matrix (Re: [R] R hang-up using lm)
GB == Göran Broström [EMAIL PROTECTED] on Wed, 28 Apr 2004 16:00:17 +0200 writes: . GB so, model.matrix(x ~ y) GB(Intercept) 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 GB attr(,assign) [1] 0 GB but model.matrix(x ~ as.vector(y)) GB(Intercept) as.vector(y) 1 1 -0.853357506 2 1 GB -0.711872147 3 1 -0.228785137 4 1 -0.449739758 5 1 GB 0.173914266 6 1 -0.138766243 7 1 -0.433799800 8 1 GB 0.234183701 9 1 0.002728104 10 1 0.733590165 GB attr(,assign) [1] 0 1 GB AND rr - model.matrix.default(x ~ y) GB Segmenteringsfel [EMAIL PROTECTED]:~$ .. GB (Don't ask me what's going on: but 'Segmenteringsfel' GB means 'Segmentation fault':) Thank you, Göran. Yes, the bug is in model.matrix.default(); one part of the problems happens in the line ans - .Internal(model.matrix(t, data)) (which only returns the intercept part). How to fix this is not yet clear to me, since we have to decide if the internal C code should do more checking or the R code in model.matrix.default. BTW, a very simple reproducible example is x - 1:7; y. - x ; y - array(y, 7) model.matrix(x ~ y) # which behaves badly when called repeatedly; # which for me means memory allocation problems ## as opposed to model.matrix(x ~ y.) # which is all fine I'll also file this as bug report. Martin __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Problem in Installing Package from CRAN...
Hi,
I have installed R 1.9.0 under Windows XP. When I used
Packages-Install Package(s) from CRAN... to install the package 'gregmisc', I got
this message:
local({a - CRAN.packages()
+ install.packages(select.list(a[,1],,TRUE), .libPaths()[1], available=a)})
trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/PACKAGES'
Content type `text/plain; charset=iso-8859-1' length 17113 bytes
opened URL
downloaded 16Kb
trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/gregmisc_0.10.2.zip'
Content type `application/zip' length 594089 bytes
opened URL
downloaded 580Kb
Error in unpackPkg(foundpkgs[okp, 2], pkgnames[okp], lib, installWithVers) :
Unable to create temp directory C:/PROGRA~1/R/rw1090/library\file2869
Thanks in advance for any help.
Minghua
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Re: [R] Problem in Installing Package from CRAN...
Your user is not within administrators group. Try with the user administrator. A.S. Alessandro Semeria Models and Simulations Laboratory Montecatini Environmental Research Center (Edison Group), Via Ciro Menotti 48, 48023 Marina di Ravenna (RA), Italy Tel. +39 544 536811 Fax. +39 544 538663 E-mail: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Problem in Installing Package from CRAN...
Do you have write permission in C:/PROGRA~1/R/rw1090/library? If not (and
it seems not), then you need to install elsewhere.
This *is* covered in the rw-FAQ: please consult the posting guide.
On Wed, 28 Apr 2004, Yao, Minghua wrote:
Hi,
I have installed R 1.9.0 under Windows XP. When I used
Packages-Install Package(s) from CRAN... to install the package 'gregmisc', I got
this message:
local({a - CRAN.packages()
+ install.packages(select.list(a[,1],,TRUE), .libPaths()[1], available=a)})
trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/PACKAGES'
Content type `text/plain; charset=iso-8859-1' length 17113 bytes
opened URL
downloaded 16Kb
trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/gregmisc_0.10.2.zip'
Content type `application/zip' length 594089 bytes
opened URL
downloaded 580Kb
Error in unpackPkg(foundpkgs[okp, 2], pkgnames[okp], lib, installWithVers) :
Unable to create temp directory C:/PROGRA~1/R/rw1090/library\file2869
Thanks in advance for any help.
Minghua
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Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
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Re: [R] p-values
On Tue, 27 Apr 2004 22:25:22 +0100 (BST) (Ted Harding) [EMAIL PROTECTED] wrote: On 27-Apr-04 Greg Tarpinian wrote: I apologize if this question is not completely appropriate for this list. Never mind! (I'm only hoping that my response is ... ) [...] This week I have been reading Testing Precise Hypotheses by J.O. Berger Mohan Delampady, Statistical Science, Vol. 2, No. 3, 317-355 and Bayesian Analysis: A Look at Today and Thoughts of Tomorrow by J.O. Berger, JASA, Vol. 95, No. 452, p. 1269 - 1276, both as supplements to my Math Stat. course. It appears, based on these articles, that p-values are more or less useless. . . . I don't have these articles available, but I'm guessing that they stress the Bayesian approach to inference. Saying p-values are more or less useless is controversial. Bayesians consider p-values to be approximately irrelevant to the real question, which is what you can say about the probability that a hypothesis is true/false, or what is the probability that a parameter lies in a particular range (sometimes the same question); and the probability they refer to is a posterior probability distribution on hypotheses, or over parameter values. The P-value which is emitted at the end of standard analysis is not such a probability, but instead is that part of a distribution over the sample space which is defined by a cut-off value of a test statistic calculated from the data. So they are different entities. Numerically they may coincide; indeed, for statistical problems with a certain structure the P-value is equal to the Bayesian posterior probability when a particular prior distribution is adopted. If this is indeed the case, then why is a p-value typically given as a default output? For example, I know that PROC MIXED and lme( ) both yield p-values for fixed effects terms. P-values are not as useless as sometimes claimed. They at least offer a measure of discrepancy between data and hypothesis (the smaller the P-value, the more discrepant the data), and they offer this measure on a standard scale, the probabiltiy scale -- the chance of getting something at least as discrepant, if the hypothesis being tested is true. What discrepant objectively means is defined by the test statistic used in calculating the P-value: larger values of the test statistic correspond to more discrepant data. Ted, this opens up a can of worms, depending on what you mean by discrepant and even data (something conditioned upon or a stochastic quantity that we happen to only be looking at one copy of?). I think your statement plays into some of the severe difficulties with P-values, especially large P-values. Confidence intervals are essentially aggregates of hypotheses which have not been rejected at a significance level equal to 1 minus the P-value. The P-value/confidence-interval approach (often called the frequentist approach) gives results which do not depend on assuming any prior distribution on the parameters/hypotheses, and therefore could be called objective in that they avoid being accused of importing subjective information into the inference in the form of a Bayesion prior distribution. They are objective only in the sense that subjectivity is deferred in a difficult to document way when P-values are translated into decisions. This can have the consequence that your confidence interval may include values in a range which, a priori, you do not acept as plausible; or exclude a range of values in which you are a priori confident that the real value lies. The Bayesian comment on this situation is that the frequentist approach is incoherent, to which the frequentist might respond well, I just got an unlucky experiment this time (which is bound to occur with due frequency). The theory I am learning does not seem to match what is commonly available in the software, and I am just wondering why. The standard ritual for evaluating statistical estimates and hypothesis tests is frequentist (as above). Rightly interpreted, it is by no means useless. For complex historical reasons, it has become the norm in research methodology, and this is essentially why it is provided by the standard software packages (otherwise pharmaceutical companies would never buy the software, since they need this in order to get past the FDA or other regulatory authority). However, because this is the norm, such results often have more meaning attributed to them than they can support, by people disinclined to delve into what rightly interpreted might mean. The statement that frequentist methods are the norm, which I'm afraid is usually true, is a sad comment on the state of much of scientific inquiry. IMHO P-values are so defective that the imperfect Bayesian approach should be seriously entertained. This is not a really clean answer to your question; but then your question touches on complex and
Re: [R] coding of categories in rpart
On Tue, 27 Apr 2004, Prabhakar Krishnamurthy wrote: I am using rpart to derive classification rules for customer segments. I have a few categorical variables in the set of independent variables. For instance, Account Size can be (Very-Small, Small, Medium, Large, V-Large) Rpart seems to encode these categories into: a,b,c,d,e It doesn't. That is one output representation (of several), of the factor levels. The results are expressed in terms of the encoded values. How do I find out what encoding was used by rpart. i.e. what categories in my input set do a, b, c,... correspond to? By reading the documentation! E.g. ?text.rpart. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Possible bug in foreign library import of Stata datasets
On Wed, 28 Apr 2004, Peter Dalgaard wrote: Looks like a classic signed/unsigned confusion. Negative numbers stored in ones-complement format in single bytes, but getting interpreted as unsigned. A bug report could be a good idea if the resident Stata expert (Thomas, I believe) is unavailable just now. Yes, it's a simple signed/unsigned bug. We carefully read in the 2-byte and 4-byte types as unsigned int so we can use and to do byte swapping, but of course this doesn't work for the 1-byte type. There's the additional problem that sometimes we want to read an unsigned byte of meta-data. -thomas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Possible bug in foreign library import of Stata datasets
On Wed, 28 Apr 2004, Paul Johnson wrote: The read.dta has translated the negative values as (256-deml). Is this the kind of thing that is a bug, or have I missed something in the documentation about the handling of negative numbers? Should a formal bug report be filed? A fixed version of the foreign package has been sent to CRAN. -thomas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Fedora 1 RPM Packages
On Wed, 2004-04-28 at 07:12, Prof Brian Ripley wrote:
I think this is appropriate for most users: if you want to use
--enable-R-shlib you can and probably should compile R yourself. (After
all, you are going to need the development tools for almost all uses of
libR.so.) It is not a zero-cost option: it does for example cause shared
objects in packages to be linked against libR.so not R.bin and so
increases considerably the run-time footprint.
From the response that I have had from the list it appears that not many
people use the shared lib from R, and that it wouldn't make sense to
build it that way by default.
I'll drop trying to get this added. If it's only a handful of us who
are using PL/R (PostgresQL procedural language) we'll have to just
recompile the source RPM. Which is no big deal.
Thanks for the responses. Now off to the real work of getting some data
in PostgresQL and taking a look at it!
cheers
ian
On Tue, 27 Apr 2004, Ian Wallace wrote:
Don't know if this is the correct place to post this question however I
thought I would start here. The Fedora 1 packages are built without the
option '--enable-R-shlib' turned on in the R.spec file. Other software,
like, plr (the postgresql library that calls R) needs the shared lib.
Any chance that we can change the R.spec file to include:
[EMAIL PROTECTED] SPECS]$ diff -bu R.spec R.spec.orig
--- R.spec 2004-04-27 15:31:51.0 -0600
+++ R.spec.orig 2004-04-27 15:31:39.0 -0600
@@ -36,7 +36,6 @@
%build
export R_BROWSER=/usr/bin/mozilla
( %configure \
---enable-R-shlib \
--with-tcl-config=%{_libdir}/tclConfig.sh \
--with-tk-config=%{_libdir}/tkConfig.sh ) \
| egrep '^R is now|^ |^$' - CAPABILITIES
I'm not sure if there are other issues with using the shared library,
I'm very new to R and just joined the mailing list.
Thanks!
ian
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Re: [R] installing R on Fedora Core 2 test 2
On Tue, 2004-04-27 at 17:21, Peter Dalgaard wrote: Jonathan Baron [EMAIL PROTECTED] writes: The one thing I cannot figure out is that readline does not work. It was installed, but apparently not detected. Grepping config.site for readline gets stuff like this: configure:21256: checking for rl_callback_read_char in -lreadline configure:21286: gcc -o conftest -g -O2 -I/usr/local/include -L/usr/local/lib conftest.c -lreadline -ldl -lncurses -lm 5 /usr/bin/ld: cannot find -lreadline Hm? The usual problem is that people forget to install readline-devel, but is that the expected error message then? Could you do an rpm -ql readline and see where the libreadline stuff went to? If you did forget readline-devel, try that first of course. BTW, it might be a good idea to see if you can rpm --rebuild from Martyn's src.rpm. That gives you your very own .rpm, which you can install and eventually upgrade (which is the point) using the standard tools. The RPM also has a patched shell script that sets LANG=C so you don't get the warning about utf-8 locales not being supported (This may not worry you, but try checking an R package and you will see it can be a problem). You can check the CAPABILITIES file against my rpm for Fedora 1 (which you can download from CRAN) to make sure you got everything. I'll be moving to Fedora 2 when it is released. But the rapid release schedule of Fedora, combined with lack of binary compatibility between versions, does pose problems for me as a binary package maintainer. I think I will only maintain the current and previous releases at any given time. Martyn __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] sas vs r
At 11:39 2004-04-28, Göran Broström wrote: If I recall correctly, neither glmmML nor glmmPQL (from MASS) handles offset terms. But GLMM in the lme4 package does. glmmML handles offset terms. You're right. I confused it with glmmML's not being able to fit models with family = gaussian. Sorry. I am pretty sure that glmmPQL does too. glmmPQL doesn't complain about the offset term but ignores it. I guess that glmmPQL ignores offsets since lme, upon which glmmPQL depends, ignores offsets. //Henric __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Fedora 1 RPM Packages
From the response that I have had from the list it appears that not many people use the shared lib from R, and that it wouldn't make sense to build it that way by default. The generic answer to this kind of request is that if a feature isn't enabled by default, then it doesn't go in the RPM. Martyn __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Slicing an area....
I have interpolated a large number of data and obtained a regular x-y curve (and its interpolated function). My problem is that I need to slice the entire area delimited by the curve, the x-axis and the two finite extremes of the curve (starting from the very bottom of the entire area) into smaller stripes of given (and different) areas. How can I do it? Vittorio __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] label separators in boxplots with conditioning
Hi R-helpers, I have a data.frame with three columns (lots more reps though in each), like so: 'FOO''BAR''RESULT' 1 .0175 1 .0512 1.1.01100 1.1.0550 1.2.0175 1.2.0512 I am calling boxplot(RESULT ~ FOO:BAR, ...) This gives me the box plots I want, but on the x-axis my labels are 1.01, 1.05, 1.1.01, 1.1.05, 1.2.01, 1.2.01. I would like to separate the factors by something other than a dot for obvious reasons. I would also like to *avoid* using the 'names' parameter to boxplot (because I am lazy and want a general solution). Please cc me directly as I read the list on digest Thanks again to such a helpful list! W __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] numericDeriv
optim(..., hessian=TRUE, ...) outputs a list with a component hessian, which is the second derivative of the log(likelihood) at the minimum. If your objective function is (-log(likelihood)), then optim(..., hessian=TRUE)$hessian is the observed information matrix. If eigen(...$hessian)$values are all positive with at most a few orders of magnitude between the largest and smallest, then it is invertable, and the square roots of the diagonal elements of the inverse give standard errors for the normal approximation to the distribution of parameter estimates. With objective functions that may not always be well behaved, I find that optim sometimes stops short of the optimum. I run it with method = Nelder-Mead, BFGS, and CG, then restart the algorithm giving the best answer to one of the other algorithms. Doug Bates and Brian Ripley could probably suggest something better, but this has produced acceptable answers for me in several cases, and I did not push it beyond that. hope this helps. Jean Eid wrote: Dear All, I am trying to solve a Generalized Method of Moments problem which necessitate the gradient of moments computation to get the standard errors of estimates. I know optim does not output the gradient, but I can use numericDeriv to get that. My question is: is this the best function to do this? Thank you Jean, __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] numericDeriv
True, True, However I am not estimating via MLE. The objective function is
bunch of moment conditions weighted according to the uncertainty of the
moment ( i.e. an estimate of the asymptotic Var-Cov matrix of the moments
(not the estimates)) Technically it looks more like a weighted nonlinear
least square problem. I have a bunch of momnets that look like this
E(e_{ik} z_i)=0
where e_{ik} is the error term and is a nonlinear function
of the paramaters at observation i. . z_i is an instrument ( the model
have endogenous covariates). k above indicates that there is more than one
functional form for the residuals (simultaneous equation system that is
nonlinear). one of them look like
e_{ik}=\ln(p-{1\over \alpha} \Delta^{-1})-W\theta
There are two more.
I am interseted in estimating \alpha, \theta, (\theta \in R^{k}) in
addition to other paramaters in the other equations.
I only want to use these moment conditions rather than assuming knowledge
of the distribution oof the error term.
At the end of the day, I need to use the delta method to get at an
estimate for the standard errors.
Hope this clarifies some bit more
On Wed, 28 Apr 2004, Spencer Graves wrote:
optim(..., hessian=TRUE, ...) outputs a list with a component
hessian, which is the second derivative of the log(likelihood) at the
minimum. If your objective function is (-log(likelihood)), then
optim(..., hessian=TRUE)$hessian is the observed information matrix. If
eigen(...$hessian)$values are all positive with at most a few orders of
magnitude between the largest and smallest, then it is invertable, and
the square roots of the diagonal elements of the inverse give standard
errors for the normal approximation to the distribution of parameter
estimates. With objective functions that may not always be well
behaved, I find that optim sometimes stops short of the optimum. I run
it with method = Nelder-Mead, BFGS, and CG, then restart the
algorithm giving the best answer to one of the other algorithms. Doug
Bates and Brian Ripley could probably suggest something better, but this
has produced acceptable answers for me in several cases, and I did not
push it beyond that.
hope this helps.
Jean Eid wrote:
Dear All,
I am trying to solve a Generalized Method of Moments problem which
necessitate the gradient of moments computation to get the
standard errors of estimates.
I know optim does not output the gradient, but I can use numericDeriv to
get that. My question is: is this the best function to do this?
Thank you
Jean,
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[R] [R-pkgs] Release candidate 1 of lme4_0.6-1
Deepayan Sarkar and I have a source package of release candidate 1 of the 0.6 series of the lme4 package available at http://www.stat.wisc.edu/~bates/lme4_0.6-0-1.tar.gz This package requires Matrix_0.8-6 which has been uploaded to CRAN and should be available in a few days. A copy of the source package is available as http://www.stat.wisc.edu/~bates/Matrix_0.8-6.tar.gz Although this version of lme4 passes R CMD check on our GNU/Linux systems we have not uploaded it to CRAN because it still lacks capabilities that are available in lme4_0.5-2, which is currently on CRAN. As soon as we have all the capabilities of the 0.5 series available in the 0.6 series we will release lme4_0.6-1.tar.gz to CRAN. This version of lme4 is a complete rewrite of the data structures and algorithms for fitting linear mixed models. An incomplete draft version of a paper describing the methods is available as a vignette. Subsequent releases will contain a more polished version of this paper. The big change relative to earlier versions is that you can fit models with crossed random effects quickly and easily. For example, using the data on Scottish secondary school students achievement scores (from http://multilevel.ioe.ac.uk/softrev/) we can fit a model with random effects for both the secondary and the primary school attended as library(lme4) This package is in development. For production work use lme from package nlme or glmmPQL from package MASS. data(ScotsSec) fm1 = lme(attain ~ verbal*sex, ScotsSec, random=list(primary=~1,second=~1)) gc();system.time(lme(attain ~ verbal*sex, ScotsSec, random=list(primary=~1,second=~1))) used (Mb) gc trigger (Mb) Ncells 701438 18.81166886 31.2 Vcells 267929 2.1 786432 6.0 [1] 0.1 0.0 0.1 0.0 0.0 summary(fm1) Linear mixed-effects model fit by REML Fixed: formula AIC BIClogLik 14882.32 14925.32 -7434.162 Random effects: Groups NameVariance Std.Dev. primary (Intercept) 0.275458 0.52484 second (Intercept) 0.014748 0.12144 Residual 4.2531 2.0623 Fixed effects: Estimate Std. Error DF t value Pr(|t|) (Intercept) 5.9147e+00 7.6795e-02 3431 77.0197 2e-16 *** verbal 1.5836e-01 3.7872e-03 3431 41.8136 2e-16 *** sexF1.2155e-01 7.2413e-02 3431 1.6786 0.09332 . verbal:sexF 2.5929e-03 5.3885e-03 3431 0.4812 0.63041 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 Correlation of Fixed Effects: (Intr) verbal sexF verbal 0.177 sexF-0.482 -0.178 verbal:sexF -0.122 -0.680 0.161 Number of Observations: 3435 Number of Groups: primary second 148 19 There are other examples in the tests subdirectory. The lme function behaves as previously *with one exception*. In the model specification there is no longer any distinction between crossed or nested or partially crossed random effects. This means that for nested random effects you must ensure that every inner grouping corresponds to a unique level of the inner grouping factor. For example, in the Pixel data there are two grouping factors, Dog and Side with Side nested within Dog. You must create a new grouping factor, say DS, with unique levels for each Dog/Side combination to be able to specify a model of Side within Dog. ___ R-packages mailing list [EMAIL PROTECTED] https://www.stat.math.ethz.ch/mailman/listinfo/r-packages __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Thank you for your message.
Thank you for your e-mail message to my office. Your views are very important to me and I appreciate you taking the time to share you comments and concerns. I have asked my staff to respond to only mail that is properly identified. If you live in Kansas and have included your mailing address, you may expect a written reply from my office. Unfortunately, because of a variety of constraints, I cannot respond to you by e-mail at this time. My staff will make every effort to respond as quickly as possible. I do have a website at www.ksgovernor.org which links you to a wealth of information about services available in Kansas. I have posted new releases, position statements, and other information that will keep you advised about my administration. Students wanting to know about Kansas will find helpful facts on that page, too. To schedule an event/appointment, please submit your request by U.S. mail to: Governor's Office, The Statehouse, 300 SW 10th, Topeka, KS 66612. If you have a matter that needs immediate attention, I would encourage you to call my office at 1-800-748-4408. Thank you for your interest in my administration. Sincerely, Kathleen Sebelius Governor of the State of Kansas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] simple repeated measures model: dumb user baffled!
I am in the process of transferring from an old version of S+ to using R having used a variety of other packages in the past. I'm hugely impressed with R but it has an excellent but depressing habit of exposing that I'm not a professional statistician and has done so again. Someone has run a nice little repeated measures design on my advice, students randomised to four orders of a condition that can be N or E: four orders used: NEEN, NENE, ENEN, ENNE, ten students in each block. I've inherited the data (in SPSS but I can deal with that!) with variables like: ID GENDER ORDER C1 C2 C3 C4 RESP1 RESP2 RESP3 RESP4 ... ORDER is the order as a/b/c/d; C1:C4 has the N or E for each occasion, and RESP1:RESP4 the response variables. (There are a number of these but looking at each separately is justifiable theoretically). I've had a look around the R help and some S+ books I've got and I realise I'm seriously out of my depth and my repeated measures ANOVA knowledge is rusty and very different from the way that more modern statistics handles such designs. Can anyone point me to an idiot's guide to the syntax that would help me test: a) that there is a change (probably a fall in RESPn) over the four repeats (probable through a practice effect) b) whether that shows any sign of higher than linear change c) whether on top of that, there are N/E differences. I realise that this is probably trivially easy but I'm staring at all sorts of wonderful things in Venables Ripley (S+ 2nd ed.) and in Chambers Hastie (S, 1st ed.) but nothing is quite near enough to what I need to help me overcome my limitations! TIA, Chris __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] se.fit in predict.glm
On 27-Apr-04 Peter Dalgaard wrote: (Ted Harding) [EMAIL PROTECTED] writes: The documentation does not say definitely what p$se.fit is, only calling it Estimated standard errors. I *believe* this means, at each value of X, the SE in the estimation of P[y=1] taking account of the joint uncertainty in the estimation of 'a' and 'b' in the relation probit(P) = a + b*X Can someone confirm that this really is so? Pretty accurate, I'd say. Basically, the fitted value is a function of the estimated parameters. Asymptotically, the latter are approximately normally distributed with a small dispersion so that the function is effectively linear and you can approximate the distribution of the fitted value with a normal distribution. Hmm!! This is a bit of a minefield! I've been fitting a binomial regression g - glm(y~x, family=binomial(link=probit)) followed by a predicition p - predict.glm(g, newx, type=response, se.fit=TRUE) Plotting the fit p$fit and the inplied confidence bands p$fit +- 2*p$se.fit gave rather narrow (I thought) bands for the prediction, so I did a simulation of 20 mvrnorm draws from the joint distribution of a and b (using their SDs and correlation from summary.glm). I then plotted the corresponding curves pnorm(a + b*x) and got a set of 20 curves about half of which lay well outside the above condfidence band, some quite a long way off. (This, I must say, is what I had intuitively been expecting to find in the first place!) I then turned to the VR book, and happened on the section Problems with binomial GLMs in 7.2; and discovered profile. So this led me to confint in MASS via ?profile and ?profile.glm. The results of confint(g) gave me a and b for the lower (2.5%) and upper (97.5%) curve. When plotted, these curves lay well outside the confidence bands obtained from predict.glm and were much more realistically related to my simulations (19 of my simulated curves nicely packed the space between tthe two confint curves, and one lay just outside -- couldn't have hoped for a result more close to expectation!). Nevertheless, I don't think my data were all that few or nasty: 23 x-values, roughly equally spaced, with about 12 0/1 results at each, and numbers of responses going up as 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 4 5 8 8 9 4 10 So I tend to conclude that the predict.glm(...,se.fit=TRUE) method should perhaps be avoided in favour of using confint, though I see no indication that confint respects the covariance of the parameter estimates (intercept and slope) whereas the predict method in theory does. Maybe I'll have another go, after centering the x-values at their mean ... Anyway, comments would be appreciated! Best wishe to all, Ted. E-Mail: (Ted Harding) [EMAIL PROTECTED] Fax-to-email: +44 (0)870 167 1972 Date: 28-Apr-04 Time: 21:32:11 -- XFMail -- __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Matrix efficiency in 1.9.0 vs 1.8.1
I'm seeking some advice on effectively using the new Matrix library in R1.9.0 for operations with large dense matrices. I'm working on integral operator models (implemented numerically via matrix operations) and except for the way entries are generated, the examples below really are representative of my problem sizes. My main concern is speed of large dense matrix multiplication. In R 1.8.1 (Windows2000 Professional, dual AthlonMP 2800) a=matrix(rnorm(2500*2500),2500,2500); v=rnorm(2500); system.time(a%*%v); [1] 0.11 0.00 0.12 NA NA In R 1.9.0, same platform: a=matrix(rnorm(2500*2500),2500,2500); v=rnorm(2500); system.time(a%*%v); [1] 0.24 0.00 0.25 NA NA These differences are consistent. But using the Matrix library in 1.9.0, the discrepancy disappears library(Matrix); a=Matrix(rnorm(2500*2500),2500,2500); v=Matrix(rnorm(2500),2500,1); system.time(a%*%v); [1] 0.11 0.00 0.11 NA NA The problem is b=a/3 Error in a/3 : non-numeric argument to binary operator which seems to mean that I can't just rewrite code to use Matrix instead of matrix objects -- I would have to do lots and lots of conversions between Matrix and matrix. Am I missing a trick here somewhere, that would let me use only Matrix objects and do with them the things one can do with matrix objects? Or some other way to avoid the twofold speed hit in moving to 1.9? I've tried using the Rblas.dll for AthlonXP on CRAN, and it doesn't help. Thanks in advance, Steve Stephen P. Ellner ([EMAIL PROTECTED]) Department of Ecology and Evolutionary Biology Corson Hall, Cornell University, Ithaca NY 14853-2701 Phone (607) 254-4221FAX (607) 255-8088 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] se.fit in predict.glm
(Ted Harding) [EMAIL PROTECTED] writes: The results of confint(g) gave me a and b for the lower (2.5%) and upper (97.5%) curve. When plotted, these curves lay well outside the confidence bands obtained from predict.glm and were much more realistically related to my simulations (19 of my simulated curves nicely packed the space between tthe two confint curves, and one lay just outside -- couldn't have hoped for a result more close to expectation!). Hmm, that doesn't actually hold up mathematically... You cannot just take upper/lower limits of both parameters and combine them. Nevertheless, I don't think my data were all that few or nasty: 23 x-values, roughly equally spaced, with about 12 0/1 results at each, and numbers of responses going up as 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 2 4 5 8 8 9 4 10 So I tend to conclude that the predict.glm(...,se.fit=TRUE) method should perhaps be avoided in favour of using confint, though I see no indication that confint respects the covariance of the parameter estimates (intercept and slope) whereas the predict method in theory does. Maybe I'll have another go, after centering the x-values at their mean ... Shouldn't change anything (except maybe demonstrate the fallacy of your calculation above -- lower b's give higher p's when x is negative). Anyway, comments would be appreciated! I don't seem to get anything that drastic. Things look somewhat better if you use the link-scale estimates, but the response-scale curves are not hopeless. You do have to notice that these are pointwise CIs so having multiple curves straying outside is not necessarily a problem. Just as a sanity check, did your plots look anything like the below: y - c(0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,2,4,5,8,8,9,4,10) x - 1:23 d - data.frame(x,y,n=12) m1 - glm(cbind(y,n-y) ~ x,data=d,family=binomial(probit)) confint(m1) # +-2SE approximation library(MASS) confint(m1) # profiling x1 - with(predict(m1,se.fit=TRUE,type=response), fit+outer(se.fit,c(l=-2,u=2))) x2 - with(predict(m1,se.fit=TRUE,type=link), fit+outer(se.fit,c(l=-2,u=2))) x2 - pnorm(x2) ab - mvrnorm(20,coef(m1),vcov(m1)) matplot(x2,type=l,col=black,lwd=3,lty=1) matlines(x1,type=l,col=red,lwd=3,lty=1) matlines(pnorm(t(ab%*%rbind(1,x -- O__ Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Matrix efficiency in 1.9.0 vs 1.8.1
Stephen Ellner [EMAIL PROTECTED] writes: I'm seeking some advice on effectively using the new Matrix library in R1.9.0 for operations with large dense matrices. I'm working on integral operator models (implemented numerically via matrix operations) and except for the way entries are generated, the examples below really are representative of my problem sizes. My main concern is speed of large dense matrix multiplication. In R 1.8.1 (Windows2000 Professional, dual AthlonMP 2800) a=matrix(rnorm(2500*2500),2500,2500); v=rnorm(2500); system.time(a%*%v); [1] 0.11 0.00 0.12 NA NA In R 1.9.0, same platform: a=matrix(rnorm(2500*2500),2500,2500); v=rnorm(2500); system.time(a%*%v); [1] 0.24 0.00 0.25 NA NA These differences are consistent. But using the Matrix library in 1.9.0, the discrepancy disappears library(Matrix); a=Matrix(rnorm(2500*2500),2500,2500); v=Matrix(rnorm(2500),2500,1); system.time(a%*%v); [1] 0.11 0.00 0.11 NA NA The problem is b=a/3 Error in a/3 : non-numeric argument to binary operator which seems to mean that I can't just rewrite code to use Matrix instead of matrix objects -- I would have to do lots and lots of conversions between Matrix and matrix. Am I missing a trick here somewhere, that would let me use only Matrix objects and do with them the things one can do with matrix objects? Or some other way to avoid the twofold speed hit in moving to 1.9? The trick is waiting for the author of the Matrix package to write the methods for arithmetic operations or contributing said methods yourself. :-) Actually I want to at least e-discuss the implementation with John Chambers and other members of the R Development Core Team before doing much more implementation. There are some subtle issues about how to arrange the classes and this is usually the point where John can provide invaluable guidance. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Fedora 1 RPM Packages
That makes sense since most people will build with the defaults and that's what we'd like packages for the main stream. I'm already working around it ... but thought I would mention that some of us do like the shared library. I hadn't even given any thought though to the memory foot print and assumed it would be roughly the same, I never checked though. cheers ian On Wed, 2004-04-28 at 10:11, Martyn Plummer wrote: From the response that I have had from the list it appears that not many people use the shared lib from R, and that it wouldn't make sense to build it that way by default. The generic answer to this kind of request is that if a feature isn't enabled by default, then it doesn't go in the RPM. Martyn -- Ian Wallace [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] plot.ts
On 28 Apr 2004 at 0:46, Gabor Grothendieck wrote:
kjetil at acelerate.com writes:
I have problems getting sensible series name plotted
with the ts.plot function. It doesn't seem to
use either ylab= or xy.labels= arguments.
I ended up using
plot({arg - ts.union(gasolina.eq, PIBmensPred, PIBgrowthmens) ;
colnames(arg) - c(Gaso ,PIB, PIBgrowth);arg },
main=Gasolina eq. con crecimiento Economico,
xlab=Tiempo)
plot(
ts.union(Gaso = gasolina.eq, PIB = PIBmensPred, PIBgrowth =
PIBgrowthmens), main = Gasolina eq. con crecimiento Economico,
xlab = Tiempo )
Thanks! Then I can avoid the variable labels at all, if I want, by
using backticks:
plot(
ts.union(` ` = gasolina.eq, ` ` = PIBmensPred, ` ` =
PIBgrowthmens), main = Gasolina eq. con crecimiento Economico,
xlab = Tiempo )
However, with plot.type=s, whatever I do, I get the complete x
argument as y-label, no way to avoid it. Any solution (apart from
hacking the code, which I am about to do)?
Kjetil Halvorsen
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Re: [R] Rtemp directories accumulating over time
On 28 Apr 2004 at 13:53, Prof Brian Ripley wrote: On Tue, 27 Apr 2004 [EMAIL PROTECTED] wrote: . . I don't see why: package base is never unloaded so that hook function is never run. (Indeed, no package/namespace is unloaded except by explicit user action, in particular not when R is terminated.) So there are also other tmpdirs made by R. Why, where, and why are they not removed at exit (when their content are removed)? They are removed by R. This is a Windows-only bug, as Windows sometimes does not act on commands to remove empty directories (but only sometimes). So is there anything I can do to remedy this nuisance (apart from reinstalling a newer XP (other messages indicates that can give surprises!) or changing OS)? Kjetil Halvorsen Session temporary directories should only be left around when a session crashes. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] [R ESS]
Dear ESS/R People: I installed ESS as per the directions on the ESS page from the R-Gui Page. When I start Xemacs/ESS, the scratch window comes up but no R. Also, the special function button do not come up. Any clues as to what I'm doing wrong, please? R for Windows Thanks in advance, Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] se.fit in predict.glm
On 28-Apr-04 Peter Dalgaard wrote: Hmm, that doesn't actually hold up mathematically... You cannot just take upper/lower limits of both parameters and combine them. Yes, excuse me. I had misunderstood what 'confint' does -- I misled myself into thinking that it gave be the 'a' and 'b' for the lower and the upper curve! I don't seem to get anything that drastic. Things look somewhat better if you use the link-scale estimates, but the response-scale curves are not hopeless. You do have to notice that these are pointwise CIs so having multiple curves straying outside is not necessarily a problem. Just as a sanity check, did your plots look anything like the below: Yes, that's useful -- and it also brought to the surface the other error I'd made whereby a slip of eyesight caused me to transcribe a correlation of -0.91 as 0.91, so I was simulating from the wrong distribution ... y - c(0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,2,4,5,8,8,9,4,10) x - 1:23 d - data.frame(x,y,n=12) m1 - glm(cbind(y,n-y) ~ x,data=d,family=binomial(probit)) confint(m1) # +-2SE approximation library(MASS) confint(m1) # profiling x1 - with(predict(m1,se.fit=TRUE,type=response), fit+outer(se.fit,c(l=-2,u=2))) x2 - with(predict(m1,se.fit=TRUE,type=link), fit+outer(se.fit,c(l=-2,u=2))) x2 - pnorm(x2) ab - mvrnorm(20,coef(m1),vcov(m1)) matplot(x2,type=l,col=black,lwd=3,lty=1) matlines(x1,type=l,col=red,lwd=3,lty=1) matlines(pnorm(t(ab%*%rbind(1,x Yes, fairly similar when I do it right. Thanks for the above code. I'd also overlooked 'vcov' etc and was copying SEs and correlations from the output of 'summary.glm'. The main lesson: one shouldn't stay up too late at these things. Cheers, Ted. E-Mail: (Ted Harding) [EMAIL PROTECTED] Fax-to-email: +44 (0)870 167 1972 Date: 28-Apr-04 Time: 23:54:20 -- XFMail -- __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] [R ESS] please disregard prev. message
Wrong name in init.el Sorry, Erin __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] plot.ts
kjetil at acelerate.com writes: : plot( :ts.union(` ` = gasolina.eq, ` ` = PIBmensPred, ` ` = :PIBgrowthmens), main = Gasolina eq. con crecimiento Economico, :xlab = Tiempo ) : : However, with plot.type=s, whatever I do, I get the complete x : argument as y-label, no way to avoid it. Any solution (apart from : hacking the code, which I am about to do)? par(ann=F) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] [R ESS]
Erin Hodgess wrote: Dear ESS/R People: I installed ESS as per the directions on the ESS page from the R-Gui Page. When I start Xemacs/ESS, the scratch window comes up but no R. Also, the special function button do not come up. If the R bin folder is on your path (something like c:\Program Files\R\rw1091\bin), and ess is loaded, then it should be as simple as M-x R (I typically type ESC x R enter, because Alt is in an awkward place on my laptop). If that doesn't work, then ess probably isn't being loaded. Check the docs for recommended settings on the .xemacs\init.el file. Jason __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] [R ESS] one more thing.....
Ok. R loads up. But when I try to use Ctrl-x-o or any control/escape key in the minibuffer, I get XEmacs does not own the primary selection Any ideas, please? Thanks yet again, Erin mailto: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] (no subject)
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[R] R-crash using read.shape (maptools)
Hi List, I am trying to read a large shapefile (~37,000 polys) using read.shape [winxp, 1gig ram, dellbox). I receive the following error: AppName: rgui.exeAppVer: 1.90.30412.0ModName: maptools.dll ModVer: 1.90.30412.0 Offset: 309d The getinfo.shape returns info, and the shapefile is readable in arcmap. Any ideas on how to overcome this? Thanks Herry --- Alexander Herr - Herry __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R-crash using read.shape (maptools)
Hi Herry, On Thu, 29 Apr 2004 12:20:44 +1000, you wrote: Hi List, I am trying to read a large shapefile (~37,000 polys) using read.shape [winxp, 1gig ram, dellbox). I receive the following error: AppName: rgui.exe AppVer: 1.90.30412.0ModName: maptools.dll ModVer: 1.90.30412.0Offset: 309d The getinfo.shape returns info, and the shapefile is readable in arcmap. Any ideas on how to overcome this? Thanks Herry --- Alexander Herr - Herry __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html I've had difficulty if there is too much detail in the polygon definition (i.e. too many nodes). Try thinning the polygons and try again. Danny __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] outer
Hello,
Can anyone help explain why the following are not
equivalent?
I have written a function called cord.mag(x,y) which
takes two numbers and outputs a number.
Further I defined m=1:5, n=1:26
for(i in m) { for (j in n) print(cord.mag(i,j))}
this prints the m*n values, one on each line properly
outer(m,n,cord.mag)
this gives me a matrix of zeroes
outer(1,2,cord.mag)
this gives the right value on the other hand
Thanks
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Re:[R] p-values
This is, of course, not strictly about R. But if there should be a decision to pursue such matters on this list, then we'd need another list to which such discussion might be diverted. I've pulled Frank's Regression Modeling Stratregies down from my shelf and looked to see what he says about inferential issues. There is a suggestion, in the introduction, that modeling provides the groundwork that can be used a point of departure for a variety of inferential interpretations. As far as I can see Bayesian interpretations are never really explicitly discussed, though the word Bayesian does appear in a couple of places in the text. Frank, do you now have ideas on how you would (perhaps, in a future edition, will) push the discussion in a more overtly Bayesian direction? What might be the style of a modeling book, aimed at practical data analysts who of necessity must (mostly, at least) use off-the-shelf software, that seriously entertains the Bayesian approach? R provides a lot of help for those who want a frequentist interpretation, even to including by default the *, **, *** labeling that some of us deplore. There is no similar help for those who want at least the opportunity to place the output from a modeling exercise in a Bayesian context of some description. There is surely a strong argument for the use of a more neutral form of default output, even to the excluding of p-values, on the argument that they also push too strongly in the direction of a frequentist interpretative framework. There seems, unfortunately, to be a dearth of good ideas on how the assist the placing of output from modeling functions such as R provides in an explicitly Bayesian framework. Or is it, at least in part, that I am unaware of what is out there? That, I guess, is the point of my question to Frank. Is it just too technically demanding to go much beyond trying to get users to understand that a Bayesian credible interval can, if there is an informative prior, be very different from a frequentist CI, that they really do need to pause if there is an informative prior lurking somewhere in the undergrowth? John Maindonald. Frank Harrell wrote: They [p-values] are objective only in the sense that subjectivity is deferred in a difficult to document way when P-values are translated into decisions. The statement that frequentist methods are the norm, which I'm afraid is usually true, is a sad comment on the state of much of scientific inquiry. IMHO P-values are so defective that the imperfect Bayesian approach should be seriously entertained. John Maindonald email: [EMAIL PROTECTED] phone : +61 2 (6125)3473fax : +61 2(6125)5549 Centre for Bioinformation Science, Room 1194, John Dedman Mathematical Sciences Building (Building 27) Australian National University, Canberra ACT 0200. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
