Re: [R] Re: diamond graphs and patents
On Wed, 27-Aug-2003 at 01:40PM -0400, Alvaro Muñoz wrote: | Drs. Harrell and O'Keefe, | | | | Thank you for your suggestions. | | Although it is at odds with your beliefs, University staff working | on licensing and technology transfer believe that a patent may be a | vehicle to achieve a wide use. Wider than if it were public domain? It's probably fair to say that it is an improvement over 3D bar charts and that it can be built into point and click software more easily than, say, contour plots could. If Microsoft were to pay the university a licensing fee to incorporate such plots, then 'wide use' could result and the university would benefit. But that's a big IF. best -- Patrick Connolly HortResearch Mt Albert Auckland New Zealand Ph: +64-9 815 4200 x 7188 ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~ I have the world`s largest collection of seashells. I keep it on all the beaches of the world ... Perhaps you`ve seen it. ---Steven Wright ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~ __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Using files as connections
I have been trying to read a random sample of lines from a file into a
data frame using readLines(). The help indicates that readLines() will
start from the current line if the connection is open, but presented with
a closed connection it will open it, start from the beginning, and close
it when finished.
In the code that follows I tried to open the file before reading but
apparently without success, because the result was repeated copies of the
first line:
flines - 107165
slines - 100
selected - sort(sample(flines,slines))
strvec - rep(,slines)
file(c:/data/perry/data.csv,open=r)
isel - 0
for (iline in 1:slines) {
isel - isel + 1
cline - readLines(c:/data/perry/data.csv,n=1)
if (iline == selected[isel]) strvec[isel] - cline else
isel - isel - 1
}
close(c:/data/perry/data.csv)
sel.flows - read.table(textConnection(strvec), header=FALSE, sep=,)
There was also an error no applicable method for close.
Comments gratefully received.
Murray Jorgensen
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[R] equivalent of SAS's PROC LATTICE
Dear R helpers,
is there an equivalent of SAS's PROC LATTICE in R ?
I have a partially balanced square lattice design to study and I want to compare
lattice based analysis with the randomized complete block approach.
Thanks a lot for your help,
Arnaud
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Re: [R] Newbie graphing questions
Dear Francisco, 1. Have a look at ?Devices which (under Windows at least) lists a range of devices you can open before and between plots. 2. Use par(ask=TRUE) before you start your plots 3. Christophe Declercq provided an excellent example on this mailing list, under the topic curves with shaded areas. Search for that in the archives. Regards, Andrew C. Ward CAPE Centre Department of Chemical Engineering The University of Queensland Brisbane Qld 4072 Australia [EMAIL PROTECTED] Quoting Francisco J. Bido [EMAIL PROTECTED]: Hi everyone. R is new to me and I'm very impressed with its capabilities but still cannot figure out how to do some basic things. There seems to be no lack of documentation but finding what I need has proven difficult. Perhaps you can help. Here's what I'm after: 1. How do I create a new plot without erasing the prior one i.e., have a new window pop up with the new graph? I'm on MacOSX using the Carbon port. 2. How do I pause between plot renderings i.e., in such a way that it will draw the subsequent graph after pressing the space bar (or any other key). 3. Illustrating critical regions. Say I wanted to illustrate the critical region of a standard normal. I would need to draw a vertical line from the critical point to the curve and then shade the critical region. How do I do this in R? Thanks! -Francisco __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Re: diamond graphs and patents
My reaction when learning of a proposed patent on a new graph was: oh well, that's something I can forget about. Without a patent, code would have been available in R in a very short period of time, the statistical community would have been able to play around with it, see how it worked on various problems. If the graph proved useful it would make its way into statistical practice. With a patent none of that seems possible. Prof Munoz has had fun exploring his creation, but if any of us are to do likewise I guess we will either pay up or secretly write code and play around with diamond graphs while hidden in the basement. Getting a graph used is not that simple I think. Boxplots are now an extremely useful tool, but lets not forget that Tukey also invented the hanging rootogram. As for Microsoft getting involved, God help us. Excel still doesn't do boxplots does it? Not to mention the quality of their implementation of most of their statistical routines. Like others I welcome the contribution of those at Johns Hopkins to the debate. And they perhaps shouldn't worry about us here at R-help, who are maybe just a fringe element of open source loving anti-M$ weirdos. Then again we may be the last bastion of open scientific enquiry. David Scott _ David Scott Department of Statistics, Tamaki Campus The University of Auckland, PB 92019 AucklandNEW ZEALAND Phone: +64 9 373 7599 ext 86830 Fax: +64 9 373 7000 Email: [EMAIL PROTECTED] Graduate Officer, Department of Statistics Webmaster, New Zealand Statistical Association: http://www.stat.auckland.ac.nz/nzsa/ __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] trying to produce an array of ranks
OK, I am try to produce an array of ranks. I have a set of data (s) that looks like this rt subj 312 dave 467 dave 411 dave 383 kim 398 kim ... Now I want to make a column that is an array of the ranks of rt by subject. The closest of gotten is using the following. r - by (s, s$subj, function(d) rank(d[1])) This gets the data out with ranks but I cannot figure out how to easily extract each of the lists and turn the whole thing into a nice straight array (it is an array of lists when unclassed). I couldn't get anything working with any of the apply's or ave. Any suggestions? This seems like it should be a common task. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Using files as connections
You need to save the connection object returned by file() and then use that
object in other functions.
You need to change the appropriate lines to the following (at least):
con - file(c:/data/perry/data.csv,open=r)
cline - readLines(con,n=1)
close(con)
(I don't know if more changes are needed to get it working.)
Note that using the connection object in other functions can have side
effects on the connection object (which is how a connection remembers its
point in the file.) (Perhaps more accurately, the side effect is on the
internal system data referred to by the R connection object.)
con - textConnection(letters)
con
descriptionclass mode text
letters textConnection r text
opened can readcan write
openedyes no
readLines(con, 1)
[1] a
readLines(con, 1)
[1] b
con.saved - con
readLines(con, 1)
[1] c
readLines(con.saved, 1)
[1] d
readLines(con, 1)
[1] e
identical(con, con.saved)
[1] TRUE
showConnections()
description classmode text isopen can read can write
3 letters textConnection r text opened yesno
hope this helps,
Tony Plate
At Thursday 11:19 AM 8/28/2003 +1200, you wrote:
I have been trying to read a random sample of lines from a file into a
data frame using readLines(). The help indicates that readLines() will
start from the current line if the connection is open, but presented with
a closed connection it will open it, start from the beginning, and close
it when finished.
In the code that follows I tried to open the file before reading but
apparently without success, because the result was repeated copies of the
first line:
flines - 107165
slines - 100
selected - sort(sample(flines,slines))
strvec - rep(,slines)
file(c:/data/perry/data.csv,open=r)
isel - 0
for (iline in 1:slines) {
isel - isel + 1
cline - readLines(c:/data/perry/data.csv,n=1)
if (iline == selected[isel]) strvec[isel] - cline else
isel - isel - 1
}
close(c:/data/perry/data.csv)
sel.flows - read.table(textConnection(strvec), header=FALSE, sep=,)
There was also an error no applicable method for close.
Comments gratefully received.
Murray Jorgensen
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RE: [R] Using files as connections
You are using the connection the wrong way. You need to do something like:
fcon - file(c:/data/perry/data.csv, open=r)
for (iline in 1:slines) {
isel - isel + 1
cline - readLines(fcon, n=1)
...
}
close(fcon)
BTW, here's how I'd do it (not tested!):
strvec - rep(,slines)
selected - sort(sample(flines, slines))
skip - c(0, diff(selected) - 1)
fcon - file(c:/data/[erry/data.csv, open=r)
for (i in 1:length(skip)) {
## skip to the selected line
readLines(fcon, n=skip[i])
strvec[i] - readLines(fcon, n=1)
}
close(fcon)
HTH,
Andy
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
Sent: Wednesday, August 27, 2003 7:19 PM
To: [EMAIL PROTECTED]
Subject: [R] Using files as connections
I have been trying to read a random sample of lines from a
file into a data frame using readLines(). The help indicates
that readLines() will start from the current line if the
connection is open, but presented with a closed connection it
will open it, start from the beginning, and close it when finished.
In the code that follows I tried to open the file before
reading but apparently without success, because the result
was repeated copies of the first line:
flines - 107165
slines - 100
selected - sort(sample(flines,slines))
strvec - rep(,slines)
file(c:/data/perry/data.csv,open=r)
isel - 0
for (iline in 1:slines) {
isel - isel + 1
cline - readLines(c:/data/perry/data.csv,n=1)
if (iline == selected[isel]) strvec[isel] - cline else
isel - isel - 1
}
close(c:/data/perry/data.csv)
sel.flows - read.table(textConnection(strvec), header=FALSE, sep=,)
There was also an error no applicable method for close.
Comments gratefully received.
Murray Jorgensen
__
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[R] R workshop in Australia
Need some help with R? An R workshop, led by John Maindonald, is planned for the 1st October at the University of Southern Queensland, Toowoomba, Australia. The workshop is being organised by the Queensland branch of the Statistical Society of Australia as part of their conference. The workshop consists of a morning session with John Maindonald, the author of the forthcoming book Data Analysis and Graphics Using R: An Example-Based Approach (with John Braun) This will be followed by a closer look at some other R packages in the afternoon (Bioconductor, nlme, etc). The cost for the one-day workshop is only $50 for the whole day (includes notes, morning and afternoon tea, but not lunch). Anyone interested in attending can find out more by looking at http://www.sci.usq.edu.au/staff/dunn/qstatconf/workshops.html Registration forms are available from http://www.sci.usq.edu.au/staff/dunn/qstatconf/registration.html Anyone is, of course, welcome to attend the conference also, but it is not necessary if you just wish to attend the R workshop. -- Ross Darnell Organising committee Email: [EMAIL PROTECTED] -- Dr Peter Dunn (USQ CRICOS No. 00244B) Web:http://www.sci.usq.edu.au/staff/dunn Email: dunn @ usq.edu.au Opinions expressed are mine, not those of USQ. Obviously... __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] R workshop in Australia
Need some help with R? An R workshop, led by John Maindonald, is planned for the 1st October at the University of Southern Queensland, Toowoomba, Australia. The workshop is being organised by the Queensland branch of the Statistical Society of Australia as part of their conference. The workshop consists of a morning session with John Maindonald, the author of the forthcoming book Data Analysis and Graphics Using R: An Example-Based Approach (with John Braun) This will be followed by a closer look at some other R packages in the afternoon (Bioconductor, nlme, etc). The cost for the one-day workshop is only $50 for the whole day (includes notes, morning and afternoon tea, but not lunch). Anyone interested in attending can find out more by looking at http://www.sci.usq.edu.au/staff/dunn/qstatconf/workshops.html Registration forms are available from http://www.sci.usq.edu.au/staff/dunn/qstatconf/registration.html Anyone is, of course, welcome to attend the conference also, but it is not necessary if you just wish to attend the R workshop. -- Peter Dunn Organising committee Email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] R tools for large files
Duncan Murdoch [EMAIL PROTECTED] wrote: One complication with reading a block at a time is what to do when you read too far. It's called buffering. Not all connections can use seek() to reposition to the beginning, so you'd need to read them one character at a time, (or attach a buffer somehow, but then what about rw connections?) You don't need seek() to do buffered block-at-a-time reading. For example, you can't lseek() on a UNIX terminal, but UNIX C stdio *does* read a block at a time from a terminal. I don't see what the problem with read-write connections is supposed to be. When you want to read from such a connection, you first force out any buffered output, and then you read a buffer's worth (if available) of input. Of course the read buffer and the write buffer are separate (C stdio has traditionally got this wrong, with the perverse consequence that you have to fseek() when switching from reading to writing or vice versa, but that doesn't mean it can't be got right). To put all this in context though, remember that S was designed in a UNIX environment to work in a UNIX environment and it was always intended to exploit UNIX tools. Even on a Windows box, if you get R, you get a bunch of the usual UNIX tools with it. Amongst other things, Perl is freely available for Windows, a Perl program to read a couple of hundred thousand records and spit them out in platform binary would only be a few lines long, and R _is_ pretty good at reading binary data. It really is important that R users should be allowed to use it the way that the language was designed to be used. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Re: diamond graphs and patents
I have been reading this discussion (or debate, depends on your point of view) with great interest in the last few days. On Thu, 28 Aug 2003, David Scott wrote: My reaction when learning of a proposed patent on a new graph was: oh well, that's something I can forget about. Without a patent, code would have been available in R in a very short period of time, the statistical community would have been able to play around with it, see how it worked on various problems. If the graph proved useful it would make its way into statistical practice. With a patent none of that seems possible. Prof Munoz has had fun exploring his creation, but if any of us are to do likewise I guess we will either pay up or secretly write code and play around with diamond graphs while hidden in the basement. I agree. The question, IMHO, is not whether the diamond graph is a good visualising tool or not -- because it still remains to be seen, but on the idea of having it patented. I completely agree with Dr. Ihaka that the only reason that makes R so popular and widely used across the academia, research institutes and even many large commercial companies, is that it is free and open-sourced. It is certainly going to be interesting to write up some functions in R that draws diamond graphs, and then test them on some simulated and real world data. But as Associate Professor Scott pointed out, with a patent on diamond graph (should the application be accepted), I am not sure if this is possible. With patenting in mind, I have been think what would the world like if histograms, bargraphs, boxplots...etc. were patented by the original inventors! The idea of patenting a graph seems to me like patenting a mathematical/statistical theorem. Again, if for example the Central Limit theorem is patented, does it mean we have to pay whenever we want to make inference from it? There are many software that offers educational institution an academic license, and offers students a student license. But the thought of the possibility of having to pay for using a graph (or writing codes to draw the graph) is. Getting a graph used is not that simple I think. Boxplots are now an extremely useful tool, but lets not forget that Tukey also invented the hanging rootogram. What is a hanging rootogram? ;-D As for Microsoft getting involved, God help us. Excel still doesn't do boxplots does it? Not to mention the quality of their implementation of most of their statistical routines. Even those graphs that Excel does do, e.g. histograms, it does not do a very good job in them. It has been, what, over a decade now since the first version of Excel was released? I cannot keep myself from wondering why Excel still produces ugly graphs. -- Cheers, Kevin -- On two occasions, I have been asked [by members of Parliament], 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able to rightly apprehend the kind of confusion of ideas that could provoke such a question. -- Charles Babbage (1791-1871) From Computer Stupidities: http://rinkworks.com/stupid/ -- Ko-Kang Kevin Wang Master of Science (MSc) Student SLC Tutor and Lab Demonstrator Department of Statistics University of Auckland New Zealand Homepage: http://www.stat.auckland.ac.nz/~kwan022 Ph: 373-7599 x88475 (City) x88480 (Tamaki) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Packages
I need to install some geostatistics packages that are not in the binaries, for example gstat. I downloaded rm171 and installed, and I even added precomplied packages successfully. Unfortunately, I do not know how to add packages available as gstat. If you can spare a minute, could you give me a lead on this? Any other pointers on using R in mac os x will be greatly appreciated. Thank you so much for your time on this question, and for everything you put into rmac! EAL == Emilio A. Laca One Shields Avenue, 2306 PES Building Agronomy and Range Science[EMAIL PROTECTED] University of California fax: (530) 752-4361 Davis, California 95616(530) 754-4083 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Newbie graphing questions
Thanks Hedderik, Andrew, David and of course, you Mark. You have all been very helpful. I got good answers two 1. and 2. and arsenal of ideas for 3. Mark's solution for 3. is exactly what I was thinking about. I'm indeed very grateful. Best, -Francisco On Wednesday, August 27, 2003, at 09:36 PM, Marc Schwartz wrote: On Wed, 2003-08-27 at 17:28, Francisco J. Bido wrote: Hi everyone. R is new to me and I'm very impressed with its capabilities but still cannot figure out how to do some basic things. There seems to be no lack of documentation but finding what I need has proven difficult. Perhaps you can help. Here's what I'm after: 1. How do I create a new plot without erasing the prior one i.e., have a new window pop up with the new graph? I'm on MacOSX using the Carbon port. In general, if you want to leave the existing device open and have a new device open for a new plot, you simply call the device name that you want to open (ie. under Linux you would use X11() ) to open a new plotting device on the display. See ?Devices for more details. 2. How do I pause between plot renderings i.e., in such a way that it will draw the subsequent graph after pressing the space bar (or any other key). Set 'par(ask = TRUE)' before plotting. See ?par 3. Illustrating critical regions. Say I wanted to illustrate the critical region of a standard normal. I would need to draw a vertical line from the critical point to the curve and then shade the critical region. How do I do this in R? # Generate a sequence of x values x - seq(-3, 3, by = 0.001) # Plot normal curve over x plot(x, dnorm(x), type = l) # Define left side boundary using min(x) # and CritVal using alpha = 0.05 alpha - 0.05 CritVal - qnorm(alpha / 2) x.l - seq(min(x), CritVal, length = 100) y.l - c(dnorm(x.l), 0, 0) # add CritVal, min(x) to complete polygon x.l - c(x.l, CritVal, min(x)) # draw and fill left region polygon(x.l, y.l, density = 50) # Do the same for right side boundary using max(x) # and Crit Val CritVal - qnorm(1 - (alpha / 2)) x.r - seq(CritVal, max(x), length = 100) y.r - c(dnorm(x.r), 0, 0) # add max(x) and CritVal to complete polygon x.r - c(x.r, max(x) , CritVal) # draw and fill left region polygon(x.r, y.r, density = 50) HTH, Marc Schwartz __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Plotting asymptote possible with plot?
I am calculating LOD scores in genetic epidemiology where the number of non recombinants is 11 and recombinants is 1. I created a function to calculate the z scores for the following thetas. theta - c(0,0.01,0.05,0.10,0.20,0.45,0.5) The z scores for the respective thetas in this cases are: -Inf,1.56,2.07,2.11,1.85,0.410,0.0 I attempt to plot these values using the following commands. plot(theta, zscore, xlab = theta, ylab = LOD Score, type = l, ylim = c(-5,5), panel.first = grid(5,16), panel.last = abline(h=0),axes=F) axis(side = 1,at = c(0,.1,.2,.3,.4,.5)) axis(side = 2,at = c(-5,-4,-3,-2,-1,0,1,2,3,4,5)) The plot works but does not plot from the points (0,-Inf) to (0.01,1.56). As this is an asymptotic value, I'm unsure that the plot function can plot to -Inf. I am using R 1.7.1. on WinXP sp1. Is there a way to plot the asymptote? Regards Tom __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Packages
Could you clarify that you want to do this on the Carbon MacOS port, and not the Darwin MacOS X port? Since gstat uses Unix-like configure tools, I think this would need a _lot_ of expertise, something not worth doing for the last release of the Carbon port. If you are running MacOS X, why don't you try to do it under the Darwin port (with the right tools installed, just use install.packages(gstat)). Or you might like to wait a few days for the RAqua port of R (the Darwin port with an Aqua GUI) to go into alpha test (it will be the MacOS X port for R 1.8.0). Alternatively, could you use R on an OS that does have easy support for gstat, e.g. Windows or Linux? On Wed, 27 Aug 2003, Emilio A. Laca wrote: I need to install some geostatistics packages that are not in the binaries, for example gstat. I downloaded rm171 and installed, and I even added precomplied packages successfully. Unfortunately, I do not know how to add packages available as gstat. If you can spare a minute, could you give me a lead on this? Any other pointers on using R in mac os x will be greatly appreciated. Thank you so much for your time on this question, and for everything you put into rmac! -- 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
Re: [R] testing if two multivariate samples are from the samedistribution
Am Mittwoch, 27. August 2003 22:22 schrieb Jason Liao: Hello, everyone! I wonder if any R package can do the multivariate Smirnov test. Specifically, let x_1,..,x_n and y_1,...,y_m be multivariate vectors. I would like to test if the two samples are from the same underlying multivariate distribution. Thanks in advance. Jason See cramer.test in package cramer. L. Baringhaus __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Re: diamond graphs, patents and rootograms
Talking about Excel, you can produce excellent graphs in Excel. Yes you
have to work at it, but you can get there. The problem is that they are
not the default. My gut feeling is that R will make more of an impact in
the presentation of graphics than any implementation in Excel.
So even if a patent were granted and it made itself into a mainstream
package, would it change the world or would the people who currently use
three dee (3D) graphs think that they looked a bit square. Or would the
implementation allow us to change the colour of each diamond or maybe we
could put a picture of our daughter as a background. Does change happen
from the tool or the user.
So I guess my reason for saying R will make more of an impact is because
the average R user cares about what they are doing when compared to the
average Excel user.
also
On Thu, 28 Aug 2003, David Scott wrote:
What is a hanging rootogram? ;-D
Now I can't work out what the wink means, but they're implemented in the
VCD package
Also http://www.math.yorku.ca/SCS/vcd/vcdstory.pdf for more info
_
Tom Mulholland
Senior Policy Officer
WA Country Health Service
Tel: (08) 9222 4062
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Re: [R] trying to produce an array of ranks
Hi On 27 Aug 2003 at 20:32, John Christie wrote: OK, I am try to produce an array of ranks. I have a set of data (s) that looks like this rtsubj 312 dave 467 dave 411 dave 383 kim 398 kim ... Now I want to make a column that is an array of the ranks of rt by subject. The closest of gotten is using the following. r - by (s, s$subj, function(d) rank(d[1])) This gets the data out with ranks but I cannot figure out how to easily extract each of the lists and turn the whole thing into a nice straight array (it is an array of lists when unclassed). I couldn't get anything working with any of the apply's or ave. Any suggestions? This seems like it should be a common task. I am not sure you want to your output to look like. r[n] will give you ranks for nth person unlist(r) vill give you one vector of ranks If you want a table of ranks let say with names in the first row and ranks for each name below it it will probably need adding some NA to shorter vectors of ranks and cbinding them together, probably using for loop. something like cbind(as.vector(unlist(r[1])),c(as.vector(unlist(r[2])),NA)) Not an easy task :( Maybe sombody will come with better answer __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help Cheers Petr Pikal [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Re: diamond graphs and patents
David Scott wrote: but if any of us are to do likewise I guess we will either pay up or secretly write code and play around with diamond graphs while hidden in the basement. Okay, lets stand up and be counted: who has been writing diamond graph code? Mine's 60 lines. Like others I welcome the contribution of those at Johns Hopkins to the debate. And they perhaps shouldn't worry about us here at R-help, who are maybe just a fringe element of open source loving anti-M$ weirdos. Then again we may be the last bastion of open scientific enquiry. Is that an M$-Windows port of R I see? Or is it still anti-M$ because it isn't written in C# and .NET? Baz __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] read.spss (package foreign) and character columns
RINNER Heinrich wrote: In R: library(foreign) test - read.spss(test.sav, to.data.frame=T) test XCHAR 1 a 2 ab 3 abcde levels(test$XCHAR) [1] a ababcde Shouldn't it rather be a ab abcde (no blanks)? I think, that should be no problem since the blanks in XCHAR may be easily removed with gsub() If you have s-c(a,ab ,ab cd ) then gsub( ,,s) [1] aab abcd removes all spaces or gsub( *$,,s) [1] a abab cd removes all trailing spaces. Hope this helps! Thomas P. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Newbie graphing questions
Marc Schwartz wrote: In general, if you want to leave the existing device open and have a new device open for a new plot, you simply call the device name that you want to open (ie. under Linux you would use X11() ) to open a new plotting device on the display. See ?Devices for more details. X11() works on Windows too. Thomas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] ks.test()
Dear All
I am trying to replicate a numerical application (not computed on R) from an
article. Using, ks.test() I computed the exact D value shown in the article
but the p-values I obtain are quite different from the one shown in the
article.
The tests are performed on a sample of 37 values (please see [0] DATA
below) for truncated Exponential, Pareto and truncated LogNormal (please see
[1] FUNCTIONS below). You can find below the commands I use to compute the
tests ([2] COMMANDS) and the p-values presented in the article.
Can anyone explain the difference between these two set of p-values? Maybe
the explanation is linked to my second question: Can anyone confirm me that
p-values calculated in the Kolmogrov-Smirnov g-o-f are independent from the
family of the distribution assumed in H0?
Anderson-Darling test is also performed in the article. would anyone have
functions to calculate pvalues for exponential, lognormal, weibull, etc?
Many thanks for your help,
Franck Allaire
R 1.6.2
###
# [0] DATA # truncation point is 30 i.e. all values are above 30
###
39.7
582
439.9
47.1
83.9
41.2
893.1
192
106.2
216.7
1243.4
52.8
351.6
36.2
431.5
57.3
1602.1
822.2
260.1
58.7
6299.9
814.9
137.2
203.8
1263.5
53.7
1313
118.4
167.8
70.1
503.7
64.8
529.9
87.8
2465.4
317.9
2753.9
###
# [1] FUNCTIONS
###
#EXP
exptfit_function(x,b, plot.it = F, lty = 1){
if (mode(x) != numeric)
stop(need numeric data)
x - x[!is.na(x)]
x - sort(x)
lambda - length(x)/sum(x-b)
if(plot.it) { lines(x, dexpt(x, lambda = lambda, b = b), lty =
lty,col=red)}
result - list(lambda = lambda, b = b)
class(result) - expt
result}
dexpt-function(x,lambda,b) dexp(x-b,rate=lambda)
pexpt-function(x,lambda,b) pexp(x-b,rate=lambda)
qexpt-function(p,lambda,b) qexp(p,rate=lambda)+b
rexpt-function(n,lambda,b) rexp(n,rate=lambda)+b
#PARETO
paretofit-function(x,b, plot.it = F, lty = 1){
x - sort(x)
alpha - length(x)/sum(log(x/b))
if(plot.it) { lines(x, dpareto(x, alpha = alpha, b = b), lty =
lty,col=red)}
result - list(alpha = alpha, b = b)
class(result) - pareto
result}
dpareto-function(x, alpha,b) ifelse(xb,0,alpha*(b^alpha)/(x^(alpha+1)))
ppareto-function(x, alpha,b) ifelse(xb,0,1-(b/x)^alpha)
qpareto-function(p, alpha,b) b*exp(-log(1-p)/alpha)
rpareto-function(n, alpha,b) qpareto(runif(n),alpha=alpha,b=b)
#LN
lnormtfit_function(x,b, plot.it = F, lty = 1){
if (mode(x) != numeric)
stop(need numeric data)
x - x[!is.na(x)]
x - sort(x)
y - log(x-b)
n - length(y)
mu - mean(y)
sigma - sd(y)
if(plot.it) { lines(x, dlnormt(x, meanlog=mu,sdlog=sigma,b=b), lty
= lty,col=red)}
result - list(mu=mu,sigma=sigma,b=b)
class(result) - lnormt
result}
dlnormt-function(x,mu,sigma,b) dlnorm(x-b,meanlog=mu,sdlog=sigma)
plnormt-function(x,mu,sigma,b) plnorm(x-b,meanlog=mu,sdlog=sigma)
qlnormt-function(p,mu,sigma,b) qlnorm(p,meanlog=mu,sdlog=sigma)+b
rlnormt-function(n,mu,sigma,b) rlnorm(n,meanlog=mu,sdlog=sigma)+b
###
# [2] COMMANDS
###
# EXP
tmp - exptfit(data,b=30)
ks.test(data,pexpt,lambda=tmp$lambda,b=tmp$b)
# Article: D= 0.2599 pvalue0.005
# PARETO
tmp - paretofit(data,b=30)
ks.test(data, ppareto, alpha=tmp$alpha,b=tmp$b)
# Article: D=0.14586 pvalue=0.16
# LN
tmp - lnormtfit(data,b=30)
ks.test(data,plnormt,mu=tmp$mu,sigma=tmp$sigma,b=tmp$b)
# Article: D=0.07939 pvalue0.15
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Re: [R] Newbie graphing questions
Thomas Petzoldt [EMAIL PROTECTED] writes: Marc Schwartz wrote: In general, if you want to leave the existing device open and have a new device open for a new plot, you simply call the device name that you want to open (ie. under Linux you would use X11() ) to open a new plotting device on the display. See ?Devices for more details. X11() works on Windows too. ..but the orig. poster was using a Mac. -- 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
Re: [R] ks.test()
You appear to be applying the KS test after estimating parameters. The
distribution theory is for an iid sample from a known continuous
distribution (and does not otherwise depend on the distribution). Since
your H_0 is not pre-specified, that distribution theory is not correct.
(Some corrections have been worked out for say ML fitting of exponential
and normal distributions -- by Michael Stephens as I recall.)
Also, your `truncated LogNormal' does not appear to be truncated, rather
to be shifted. That's the same thing for an exponential (for a positive
shift), but not for any other distribution.
On Thu, 28 Aug 2003, franck allaire wrote:
Dear All
I am trying to replicate a numerical application (not computed on R) from an
article. Using, ks.test() I computed the exact D value shown in the article
but the p-values I obtain are quite different from the one shown in the
article.
And what is the H_0 and H_1 used in the article?
The tests are performed on a sample of 37 values (please see [0] DATA
below) for truncated Exponential, Pareto and truncated LogNormal (please see
[1] FUNCTIONS below). You can find below the commands I use to compute the
tests ([2] COMMANDS) and the p-values presented in the article.
Can anyone explain the difference between these two set of p-values? Maybe
the explanation is linked to my second question: Can anyone confirm me that
p-values calculated in the Kolmogrov-Smirnov g-o-f are independent from the
family of the distribution assumed in H0?
Anderson-Darling test is also performed in the article. would anyone have
functions to calculate pvalues for exponential, lognormal, weibull, etc?
Many thanks for your help,
Franck Allaire
R 1.6.2
###
# [0] DATA # truncation point is 30 i.e. all values are above 30
###
39.7
582
439.9
47.1
83.9
41.2
893.1
192
106.2
216.7
1243.4
52.8
351.6
36.2
431.5
57.3
1602.1
822.2
260.1
58.7
6299.9
814.9
137.2
203.8
1263.5
53.7
1313
118.4
167.8
70.1
503.7
64.8
529.9
87.8
2465.4
317.9
2753.9
###
# [1] FUNCTIONS
###
#EXP
exptfit_function(x,b, plot.it = F, lty = 1){
if (mode(x) != numeric)
stop(need numeric data)
x - x[!is.na(x)]
x - sort(x)
lambda - length(x)/sum(x-b)
if(plot.it) { lines(x, dexpt(x, lambda = lambda, b = b), lty =
lty,col=red)}
result - list(lambda = lambda, b = b)
class(result) - expt
result}
dexpt-function(x,lambda,b) dexp(x-b,rate=lambda)
pexpt-function(x,lambda,b) pexp(x-b,rate=lambda)
qexpt-function(p,lambda,b) qexp(p,rate=lambda)+b
rexpt-function(n,lambda,b) rexp(n,rate=lambda)+b
#PARETO
paretofit-function(x,b, plot.it = F, lty = 1){
x - sort(x)
alpha - length(x)/sum(log(x/b))
if(plot.it) { lines(x, dpareto(x, alpha = alpha, b = b), lty =
lty,col=red)}
result - list(alpha = alpha, b = b)
class(result) - pareto
result}
dpareto-function(x, alpha,b) ifelse(xb,0,alpha*(b^alpha)/(x^(alpha+1)))
ppareto-function(x, alpha,b) ifelse(xb,0,1-(b/x)^alpha)
qpareto-function(p, alpha,b) b*exp(-log(1-p)/alpha)
rpareto-function(n, alpha,b) qpareto(runif(n),alpha=alpha,b=b)
#LN
lnormtfit_function(x,b, plot.it = F, lty = 1){
if (mode(x) != numeric)
stop(need numeric data)
x - x[!is.na(x)]
x - sort(x)
y - log(x-b)
n - length(y)
mu - mean(y)
sigma - sd(y)
if(plot.it) { lines(x, dlnormt(x, meanlog=mu,sdlog=sigma,b=b), lty
= lty,col=red)}
result - list(mu=mu,sigma=sigma,b=b)
class(result) - lnormt
result}
dlnormt-function(x,mu,sigma,b) dlnorm(x-b,meanlog=mu,sdlog=sigma)
plnormt-function(x,mu,sigma,b) plnorm(x-b,meanlog=mu,sdlog=sigma)
qlnormt-function(p,mu,sigma,b) qlnorm(p,meanlog=mu,sdlog=sigma)+b
rlnormt-function(n,mu,sigma,b) rlnorm(n,meanlog=mu,sdlog=sigma)+b
###
# [2] COMMANDS
###
# EXP
tmp - exptfit(data,b=30)
ks.test(data,pexpt,lambda=tmp$lambda,b=tmp$b)
# Article: D= 0.2599 pvalue0.005
# PARETO
tmp - paretofit(data,b=30)
ks.test(data, ppareto, alpha=tmp$alpha,b=tmp$b)
# Article: D=0.14586 pvalue=0.16
# LN
tmp - lnormtfit(data,b=30)
ks.test(data,plnormt,mu=tmp$mu,sigma=tmp$sigma,b=tmp$b)
# Article: D=0.07939 pvalue0.15
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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
__
[EMAIL
RE: [R] read.spss (package foreign) and character columns
Thanks to Brian Ripley, Douglas Bates and Thomas Petzoldt for their comments. I agree that it is not really a problem, as you can easily use sub() after read.spss() to get rid of the blanks (I had already done that). On the other hand, it might be important to _know_ about the fact that characters are filled with blanks here. [I noticed it because I used a character variable as the common column in a merge(tab1,tab2,by=XCHAR), where tab1 came into R from an SPSS file using read.spss(), and tab2 came into R from an Excel file via odbc using odbcConnectExcel(). The merge failed on some cases, because some values of XCHAR from tab1 had trailing blanks, the values of tab2 had none.] I know now, so I know what to do in future cases. But as not everybody else might be aware of this, my suggestion would be that it could be worth adding a short comment about this in help(read.spss), so noone will be surprised. Regards, Heinrich. -Ursprüngliche Nachricht- Von: RINNER Heinrich [mailto:[EMAIL PROTECTED] Gesendet: Mittwoch, 27. August 2003 18:06 An: '[EMAIL PROTECTED]' Betreff: [R] read.spss (package foreign) and character columns Dear R users! I am using R Version 1.7.1, Windows XP, package foreign (Version: 0.6-1), SPSS 11.5.1. There is one thing I noticed with read.spss, and I'd like to ask if this is considered to be a feature, or possibly a bug: When reading character columns, character strings seem to get filled with blanks at the end. Simple example: In SPSS, create a file with one variable called xchar of type A5 (character of length 5), and 3 values (a, ab, abcde), save it as test.sav. In R: library(foreign) test - read.spss(test.sav, to.data.frame=T) test XCHAR 1 a 2 ab 3 abcde levels(test$XCHAR) [1] a ababcde Shouldn't it rather be a ab abcde (no blanks)? -Heinrich. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] ks.test()
On Thu, 28 Aug 2003, Prof Brian Ripley wrote: You appear to be applying the KS test after estimating parameters. The distribution theory is for an iid sample from a known continuous distribution (and does not otherwise depend on the distribution). Since your H_0 is not pre-specified, that distribution theory is not correct. (Some corrections have been worked out for say ML fitting of exponential and normal distributions -- by Michael Stephens as I recall.) Just to amplify this comment a bit, I'm a little worried that the current documentation of of ks.test may make it appear that estimated parameters are ok, or that somehow the p-values computed are corrected in some way for their existence -- which I very much doubt. The standard reference on this sort of thing was Durbin's (1973) SIAM monograph. There is a very nice approach due to Khmaladze (1981) based on the Doob-Meyer decomposition - this is the closest thing that I'm aware of for handling KS type tests with estimated parameters in a general context. url:www.econ.uiuc.edu/~roger/my.htmlRoger Koenker email [EMAIL PROTECTED] Department of Economics vox:217-333-4558University of Illinois fax:217-244-6678Champaign, IL 61820 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] ks.test()
With the Shifted Exponential test, H_0 is data is a sample coming from a Shifted Exponential distribution with shift=30 and lambda = 0.001566907 You appear to be applying the KS test after estimating parameters. I do in order to define H_0 as explained above The distribution theory is for an iid sample from a known continuous distribution (and does not otherwise depend on the distribution). That's what I thougth but this is not what I understand reading: http://www.isi.edu/~kclan/paper/ramp/node11.html Since your H_0 is not pre-specified, that distribution theory is not correct. please see above (Some corrections have been worked out for say ML fitting of exponential and normal distributions -- by Michael Stephens as I recall.) Also, your `truncated LogNormal' does not appear to be truncated, rather to be shifted. That's the same thing for an exponential (for a positive shift), but not for any other distribution. Thanks for this clarification And what is the H_0 and H_1 used in the article? H_1 is that the sample is not coming from the specified distribution in H_0 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] ks.test()
On Thu, 28 Aug 2003, franck allaire wrote: With the Shifted Exponential test, H_0 is data is a sample coming from a Shifted Exponential distribution with shift=30 and lambda = 0.001566907 You got that after looking at the data. H_0 has to be specified before looking at the data. You appear to be applying the KS test after estimating parameters. I do in order to define H_0 as explained above That's invalid. The distribution theory is for an iid sample from a known continuous distribution (and does not otherwise depend on the distribution). That's what I thougth but this is not what I understand reading: Learn not to believe everything you read on the Web. Since your H_0 is not pre-specified, that distribution theory is not correct. please see above Rather, please take careful note yourself. (Some corrections have been worked out for say ML fitting of exponential and normal distributions -- by Michael Stephens as I recall.) Also, your `truncated LogNormal' does not appear to be truncated, rather to be shifted. That's the same thing for an exponential (for a positive shift), but not for any other distribution. Thanks for this clarification And what is the H_0 and H_1 used in the article? H_1 is that the sample is not coming from the specified distribution in H_0 Not so: perhaps an iid sample from some other continuous distribution? -- 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
[R] R-help: beginner question
Hi, I am a beginner user of R. I have a trivial question I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with read.delim() with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the boxplot help I saw that I have to declare my data with data(). I am getting errors does not matter how I am calling data(), only with the name of the table, with data(read.delim()), or in any other way. So in the end I was not able to use boxplot at all. I will appreciate any help for dummies you can give me. Also, if you know any other way to identify outliers, or to use Cook dimension to identify them, I will really appreciate. Thanks, Monica Monica Palaseanu-Lovejoy University of Manchester School of Geography Mansfield Cooper Building Oxford Road, Manchester M13 9PL, UK. email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] how to call a C program from R function
Hi all, I would like to call a C program from R function. I tried to use the .C() function without success. I need a very simple example (such as the hello program) to understand how it works. Could you give a such example? (I use the 1.7.1 Version of R with linux) Does it work in the case of a C++ program instead of a C programm? Best regards, Olivier -- - Martin Olivier INRA - Unité protéomique LIRMM - IFA/MAB 2, Place Viala 161, rue Ada F-34060 Montpellier Cédex 134392 Montpellier Cédex 5 Tel : 04 99 61 26 02 Tel : O4 67 41 86 71 [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] R-help: beginner question
Monica Palaseanu-Lovejoy [EMAIL PROTECTED] writes: I am a beginner user of R. I have a trivial question I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with read.delim() with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the boxplot help I saw that I have to declare my data with data(). I am getting errors does not matter how I am calling data(), only with the name of the table, with data(read.delim()), or in any other way. So in the end I was not able to use boxplot at all. Yours is a common problem for those starting with R. The problem is that the object that you have read, let's call it `df', is in a tabular form (called a data frame in R) and you need to specify a single column of that table as an argument to the boxplot function. There are several ways to do this. - Use the `with' function to indicate the data frame to use with(df, boxplot(TPAH16.ppm)) - Use both the name of the data frame and the name of the column, separated by $ boxplot(df$TPAH16.ppm) - Attach the data frame before creating the boxplot attach(df) boxplot(TPAH16.ppm) detach() -- Douglas Bates[EMAIL PROTECTED] Statistics Department608/262-2598 University of Wisconsin - Madisonhttp://www.stat.wisc.edu/~bates/ __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] how to call a C program from R function
Martin Olivier wrote:
Hi all,
I would like to call a C program from R function. I tried to use the
.C() function
without success. I need a very simple example (such as the hello
program) to understand
Do you want to call a C program (executable) or a shared library? If you
want to run a compiled program simply use system() or shell()
how it works. Could you give a such example?
(I use the 1.7.1 Version of R with linux)
Does it work in the case of a C++ program instead of a C programm?
If you want to call a shared library (or DLL), please look into the
Manual writing R extensions and look for the convolve example.
For a very simple hello-function see the C++ example below. Please
check if you have installed the correct compiler on Linux and look into
the manual how to compile a shared library. On Linux it is:
R CMD SHLIB test.cpp
Thomas P.
---
A simple example, but there are better in the docs ;-) e.g. building a
package.
===
// File test.cpp:
#include R.h
#include Rinternals.h
extern C {
void testarr(int* n, double* x) {
for (int i = 0; i *n; i++) {
x[i] = 2 * i;
}
}
}
===
## file test.R
dyn.load(test.so)
testarr - function(x) {
.C(testarr, as.integer(length(x)), x=as.double(x))$x
}
print(testarr(1:10))
dyn.unload(test.so)
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[R] R-help: beginner question - Thank you! OUTLIERS
Hi, Thank you so much for all your rapid answers. I am impressed. What i didn't know was that i have to assign my data to an object to work further on. It was not clear from the help (at least for me) that 'data()' itself is calling data already in R packages. All of you make that clear. Now, if you can suggest any good package to use for identifying outliers it will be great ;-)) Hopefully from now one, since i understood how i am using the examples, what 'data()' means and how i am using my own data, i will put less trivial questions. thank you so much indeed, Monica Monica Palaseanu-Lovejoy University of Manchester School of Geography Mansfield Cooper Building Oxford Road, Manchester M13 9PL, UK. email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] R-help: beginner question
Monica Palaseanu-Lovejoy [EMAIL PROTECTED] writes: Hi, I am a beginner user of R. I have a trivial question I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with read.delim() with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the boxplot help I saw that I have to declare my data with data(). I am getting errors does not matter how I am calling data(), only with the name of the table, with data(read.delim()), or in any other way. So in the end I was not able to use boxplot at all. I will appreciate any help for dummies you can give me. Also, if you know any other way to identify outliers, or to use Cook dimension to identify them, I will really appreciate. You don't need data() that's just to get some standard data for the boxplot() example. What you need is mydata - read.delim(...whatever...) attach(mydata) boxplot(V5) # or whatever col.5 is called or with(mydata, boxplot(V5)) or boxplot(mydata$V5) (Almost all the boxplot examples appear to be using the formula interface, which doesn't work without a grouping variable, and only the formula interface allows you to give a data= argument to boxplot(). At least one of those should probably be fixed.) -- 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
Re: [R] R-help: beginner question
If you read the data into a data frame, you should be able to simply pass the name of the data frame in a call to boxplot. my.data - read.delim(mytext.txt) boxplot(my.data) If you only want a boxplot of column 5 boxplot(my.data[,5]) See ?boxplot for other options to make the boxplot look the way you like. HTH, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 Monica Palaseanu-Lovejoy [EMAIL PROTECTED] 08/28/03 09:35AM Hi, I am a beginner user of R. I have a trivial question * I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with 'read.delim()' with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the boxplot help I saw that I have to declare my data with 'data()'. I am getting errors does not matter how I am calling 'data()', only with the name of the table, with data(read.delim()), or in any other way. So in the end I was not able to use boxplot at all. I will appreciate any help for dummies you can give me. Also, if you know any other way to identify outliers, or to use Cook dimension to identify them, I will really appreciate. Thanks, Monica Monica Palaseanu-Lovejoy University of Manchester School of Geography Mansfield Cooper Building Oxford Road, Manchester M13 9PL, UK. email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] how to call a C program from R function
On Thu, 28 Aug 2003, Martin Olivier wrote: Hi all, I would like to call a C program from R function. I tried to use the .C() function without success. I need a very simple example (such as the hello program) to understand how it works. Could you give a such example? There is one in Writing R Extensions. `Hello world' be too simple: you do need to know how to return results. (I use the 1.7.1 Version of R with linux) Does it work in the case of a C++ program instead of a C programm? See Writing R extensions for details and examples. -- 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
[R] (no subject)
Dear All, A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default one, 1/1024=0.000976563. Is there any way of setting the new minfactor to a lower level? 2. Is it possible to set some constraints upon the parameters to be estimated in a nls regression? Thanks, Giovanni __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] R-help: beginner question - Thank you! OUTLIERS
Have you considered normal probability plots (qqnorm) to identify outliers? These will identify much more, of course, including the need for transformations, mixtures of distributions, etc. hope this helps. spencer graves Monica Palaseanu-Lovejoy wrote: Hi, Thank you so much for all your rapid answers. I am impressed. What i didn't know was that i have to assign my data to an object to work further on. It was not clear from the help (at least for me) that 'data()' itself is calling data already in R packages. All of you make that clear. Now, if you can suggest any good package to use for identifying outliers it will be great ;-)) Hopefully from now one, since i understood how i am using the examples, what 'data()' means and how i am using my own data, i will put less trivial questions. thank you so much indeed, Monica Monica Palaseanu-Lovejoy University of Manchester School of Geography Mansfield Cooper Building Oxford Road, Manchester M13 9PL, UK. email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] (no subject)
giovanni caggiano [EMAIL PROTECTED] writes: Dear All, A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default one, 1/1024=0.000976563. Is there any way of setting the new minfactor to a lower level? I suspect you didn't quite understand how to do it: ctl.obj - nls.control(minFactor = 1/4096) nls(., control=ctl.obj) -- 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
Re: [R] nls problems (formerly no subject)
Please use an informative subject line. The r-help archives at www.r-project.org - search - R site search indexes that, and I find answers to today's problems in the r-help discussions of yesterday's questions. Only yesterday, I was got essentially that error message. I solved it by setting trace=TRUE and studying which paramters were moving. With that information, I looked at the function and thought of ways to reparameterize it to make things more stable. That helped but did not solve the problem. Ultimately, I fixed two of the most volatile parameters to sensible values. Then nls gave me answers very quickly. An excellent reference on nonlinear regression is Bates and Watts (1988) Nonlinear regression and its applications (Wiley). They talk some about reparameterizations. A major contribution of this book is distinguishing between the intrinsic nonlinearity of the problem, which cannot be fixed without changing the model, and parameter effect curvature, which can be fixed by just writing the model in a different but equivalent way. Pages 256-259 summarize some 67 different examples from published literature. In each case, parameter effects curvature was more than the intrinsic curvature, with the median being a factor of 16 larger. For my problem yesterday, I did not just restrict myself to reparameterizations: I also considered alternative models with similar but formally different behavior. Also, have you considered using optim first, then feeding the answers to nls? McCullough found a few years ago that it was easier for him to get answers if he did it that way, because the S-Plus versions of nls seems to get lost and quit prematurely, while optim will at least produce an answer. If I'm not mistaken, this issue is discussed in either McCullough, B. D. (1999) Assessing the reliability of statistical software: Part II The American Statistician, 53, 149-159 or McCullough, B. D. (1998) Assessing the reliability of statistical software: Part I The American Statistician, 52, 358-366. I don't remember now which paper had this, but I believe one of them did; I think I'd look at the second first. (McCullough discussed nlminb instead of optim. The former has been replaced by the latter in R.) hope this helps. spencer graves giovanni caggiano wrote: Dear All, A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default one, 1/1024=0.000976563. Is there any way of setting the new minfactor to a lower level? 2. Is it possible to set some constraints upon the parameters to be estimated in a nls regression? Thanks, Giovanni __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Cook-distance-type plot (vertical bars)
Hi, Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. The lower right-hand plot is labelled Cook's distance plot, and I'd really like to produce a similar type of figure, but in a totally different context. (I'm not even sure what this kind of figure is called, perhaps an impulse plot, where instead of a point at (x,y), there's a vertical bar running from the x-axis up to where the point would be). Can anyone give me pointers on where to look for more info. I've had a look in the places I could think of (plot.lm.R, termplot.R, plot.R, aov.R), and couldn't find anything. Maybe I overlooked it? Thanks -Frank Gibbons PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] nls minFactor and constraints [was (no subject)]
giovanni caggiano [EMAIL PROTECTED] writes: A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default one, 1/1024=0.000976563. Is there any way of setting the new minfactor to a lower level? You need to set control=nls.control(minFactor=1/4096) in the call to nls. 2. Is it possible to set some constraints upon the parameters to be estimated in a nls regression? Other than by parameter transformation, no. See section 3.4.1 of Bates and Watts (1988), Nonlinear Regression Analysis and Its Applications, Wiley to see how to use parameter transformations for this. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Cook-distance-type plot (vertical bars)
On Thu, 28 Aug 2003, Frank Gibbons wrote: Hi, Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. The lower right-hand plot is labelled Cook's distance plot, and I'd really like to produce a similar type of figure, but in a totally different context. (I'm not even sure what this kind of figure is called, perhaps an impulse plot, where instead of a point at (x,y), there's a vertical bar running from the x-axis up to where the point would be). Often called an `index plot'. It's done by plot(type=h). R seems to think that is `histogram-like', but the notation comes from S which calls it `high-density lines'. I've never found either intuitive notation. Can anyone give me pointers on where to look for more info. I've had a look in the places I could think of (plot.lm.R, termplot.R, plot.R, aov.R), and couldn't find anything. Maybe I overlooked it? I suspect it was done by plot.lm(which=4), which does an index plot of Cook's distance. -- 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
Re: [R] Cook-distance-type plot (vertical bars)
On Thu, 28 Aug 2003, Frank Gibbons wrote: Hi, Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14. The lower right-hand plot is labelled Cook's distance plot, and I'd really like to produce a similar type of figure, but in a totally different context. (I'm not even sure what this kind of figure is called, perhaps an impulse plot, where instead of a point at (x,y), there's a vertical bar running from the x-axis up to where the point would be). It's called a high-density plot, and you get it by specifying type=h in a plot() command. It's mentioned on page 31 of `R for beginners' It is in the code for plot.lm, where you say you also looked: the cook's distance plot is created with plot(cook, type = h, ylim = c(0, ymx), main = main, xlab = Obs. number, ylab = Cook's distance, ...) -thomas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] nls problems (formerly no subject)
I agree with what you said about using trace = TRUE when you are having trouble getting nls to converge. This allows you to see what is happening to the parameters during the iterations and that it is often quite instructive; as is plotting your data and thinking about whether you should expect to be able to estimate all the parameters in your model from the data that you have. The nls function is not magic. It can only use that information that is available in the data. Spencer Graves [EMAIL PROTECTED] writes: Also, have you considered using optim first, then feeding the answers to nls? McCullough found a few years ago that it was easier for him to get answers if he did it that way, because the S-Plus versions of nls seems to get lost and quit prematurely, while optim will at least produce an answer. If I'm not mistaken, this issue is discussed in either McCullough, B. D. (1999) Assessing the reliability of statistical software: Part II The American Statistician, 53, 149-159 or McCullough, B. D. (1998) Assessing the reliability of statistical software: Part I The American Statistician, 52, 358-366. I don't remember now which paper had this, but I believe one of them did; I think I'd look at the second first. (McCullough discussed nlminb instead of optim. The former has been replaced by the latter in R.) I would be hesitant to draw too many conclusions from McCullough's experiences. He used the data sets, models, and starting estimates from the NIST nonlinear least squares test sets. These are available in the NISTnls package for R. If you run the examples in that package you will see that all of the examples can be fit reasonably easily in R. However, the people at NIST decided that they wanted to create easy and difficult versions of each example and they did this by chosing one reasonable set of starting estimates nd one ridiculous set of starting estimates for each problem. Check, for example, library(NISTnls) example(Eckerle4) The model that is being fit is a scaled version of a Gaussian density. A mere glance at the data shows that the location parameter will be around 450 and the scale parameter will be around 5. There is no problem at all converging from those starting values - that's the easy version of the problem. The difficult version of the problem is to try to converge from starting estimates of 500 for the location and 10 for the scale. Look at a plot of the data. Would anyone who knew what those parameters represent consider 500 as a reasonable guess of the location of the peak? I don't feel that it is a terrible deficiency in the nls implementation in R that it does not converge on this model/data combination from those starting estimates. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] R-help: beginner question
A Guide for the Unwilling S User would help orient you to how R works. It is meant to do that as quickly and painlessly as possible. Patrick Burns Burns Statistics [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and A Guide for the Unwilling S User) Monica Palaseanu-Lovejoy wrote: Hi, I am a beginner user of R. I have a trivial question I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with read.delim() with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the boxplot help I saw that I have to declare my data with data(). I am getting errors does not matter how I am calling data(), only with the name of the table, with data(read.delim()), or in any other way. So in the end I was not able to use boxplot at all. I will appreciate any help for dummies you can give me. Also, if you know any other way to identify outliers, or to use Cook dimension to identify them, I will really appreciate. Thanks, Monica Monica Palaseanu-Lovejoy University of Manchester School of Geography Mansfield Cooper Building Oxford Road, Manchester M13 9PL, UK. email: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Cook-distance-type plot (vertical bars)
Thanks to all who responded, and so promptly too: it works exactly as you describe. Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14. Thomas Lumley is quite right, it's produced by plot() (not termplot()), and it is mentioned on p31 of R for beginners. My mistake. In the interest of self education, is there a more comprehensive source for plot-types that I should read? Ideally, this would be something with lots of figures, so that I could browse the figures to find what I want to do, and then look up how to do it. R for Beginners goes some way along this path, but perhaps there's something more comprehensive? Thanks again, -Frank PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Newbie graphing questions
The MacOSX (carbon port) command turned out to be, surprisingly enough, macintosh() Thanks! On Thursday, August 28, 2003, at 07:19 AM, Peter Dalgaard BSA wrote: Thomas Petzoldt [EMAIL PROTECTED] writes: Marc Schwartz wrote: In general, if you want to leave the existing device open and have a new device open for a new plot, you simply call the device name that you want to open (ie. under Linux you would use X11() ) to open a new plotting device on the display. See ?Devices for more details. X11() works on Windows too. ..but the orig. poster was using a Mac. -- 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 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] make dvi fails
I am working with a RedHat 9 system with gcc 3.2.2, makeinfo 4.3, and perl 5.8. I have just downloaded the latest r-patched with rsync and successfully compiled the code and passed the tests conducted with 'make check'. After that, 'make dvi' gives the following result: make dvi make[1]: Entering directory `/usr/src/R/doc' make[2]: Entering directory `/usr/src/R/doc/manual' creating doc/manual/version.tex collecting LaTeX docs for package 'base' ... make[3]: Entering directory `/usr/src/R/src/library' Building/Updating help pages for package 'base' Formats: latex make[3]: Leaving directory `/usr/src/R/src/library' collecting LaTeX docs for package 'methods' ... make[3]: Entering directory `/usr/src/R/src/library' Building/Updating help pages for package 'methods' Formats: latex make[3]: Leaving directory `/usr/src/R/src/library' collecting LaTeX docs for package 'tools' ... make[3]: Entering directory `/usr/src/R/src/library' Building/Updating help pages for package 'tools' Formats: latex make[3]: Leaving directory `/usr/src/R/src/library' make[2]: *** No rule to make target `-pkg.tex', needed by `stamp-refman-dvi'. Stop. make[2]: Leaving directory `/usr/src/R/doc/manual' make[1]: *** [dvi] Error 2 make[1]: Leaving directory `/usr/src/R/doc' make: [dvi] Error 2 (ignored) 'make pdf' gives: make pdf make[1]: Entering directory `/usr/src/R/doc' make[2]: Entering directory `/usr/src/R/doc/manual' make[2]: *** No rule to make target `-pkg.tex', needed by `stamp-refman-pdf'. Stop. make[2]: Leaving directory `/usr/src/R/doc/manual' make[1]: *** [pdf] Error 2 make[1]: Leaving directory `/usr/src/R/doc' make: [pdf] Error 2 (ignored) 'make info' works fine. Is there something wrong with the makefile? Why the No rule to make target `-pkg.tex', needed by `stamp-refman-dvi[or pdf] messages? Any idea what the problem is? -- William D. McCoy Geosciences University of Massachusetts Amherst, MA 01003 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Cook-distance-type plot (vertical bars)
Have you looked at Modern Applied Statistics with S by Venables and Ripley? hope this helps. spencer graves Frank Gibbons wrote: Thanks to all who responded, and so promptly too: it works exactly as you describe. Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14. Thomas Lumley is quite right, it's produced by plot() (not termplot()), and it is mentioned on p31 of R for beginners. My mistake. In the interest of self education, is there a more comprehensive source for plot-types that I should read? Ideally, this would be something with lots of figures, so that I could browse the figures to find what I want to do, and then look up how to do it. R for Beginners goes some way along this path, but perhaps there's something more comprehensive? Thanks again, -Frank PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Cook-distance-type plot (vertical bars)
On Thu, 28 Aug 2003, Frank Gibbons wrote: Thanks to all who responded, and so promptly too: it works exactly as you describe. Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14. Thomas Lumley is quite right, it's produced by plot() (not termplot()), and it is mentioned on p31 of R for beginners. My mistake. In the interest of self education, is there a more comprehensive source for plot-types that I should read? Ideally, this would be something with lots of figures, so that I could browse the figures to find what I want to do, and then look up how to do it. R for Beginners goes some way along this path, but perhaps there's something more comprehensive? `An Introduction to R' `Modern Applied Statistics with S' as in the R FAQ (and there may be others). -- 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
RE: [R] Cook-distance-type plot (vertical bars)
I'm (relatively) new to R myself, and recently found the documentation by Dr. William Cleveland et al at http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/ http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/software.writi ng.html It has been helpful, and covers S/Splus trellis graphics. In R, the equivalent is known as lattice graphics, and the syntax is virtually identical. Earlier today, Dr. Peter Dunn posted a notice to the R listserv announcing a workshop in Australia being led by Dr. John Maindonald... in that announcement, you will find ...John Maindonald, the author of the forthcoming book 'Data Analysis and Graphics Using R: An Example-Based Approach' (with John Braun)... so apparently there is a forthcoming book detailing the graphical capabilities of R. I'm eagerly awaiting the opportunity to buy it and digest its contents! Until then, I think the links to the .ps and .pdf files above should serve well. Best wishes, david paul P.S. - You should keep in mind that there are two classes of graphical functions in S/Splus/R: regular functions and trellis/lattice functions. They operate very differently. After using a few of each, I must say that I am very impressed with the power and flexibility of the trellis/lattice plotting functions. -Original Message- From: Frank Gibbons [mailto:[EMAIL PROTECTED] Sent: Thursday, August 28, 2003 1:53 PM To: R users Subject: Re: [R] Cook-distance-type plot (vertical bars) Thanks to all who responded, and so promptly too: it works exactly as you describe. Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14. Thomas Lumley is quite right, it's produced by plot() (not termplot()), and it is mentioned on p31 of R for beginners. My mistake. In the interest of self education, is there a more comprehensive source for plot-types that I should read? Ideally, this would be something with lots of figures, so that I could browse the figures to find what I want to do, and then look up how to do it. R for Beginners goes some way along this path, but perhaps there's something more comprehensive? Thanks again, -Frank PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] how to randomize data matrix
Dear R users: Is there a function or easier way to randomize the data between rows (considering a row as a whole unit)? For example, original data: A1 A2 A3 A4 B1 1 2 3 4 B2 5 6 7 8 B3 9 10 11 12 B4 13 14 15 16 randomized data: A1 A2 A3 A4 B4 13 14 15 16 B2 5 6 7 8 B1 1 2 3 4 B3 9 10 11 12 Thank you for your attention! Joshua __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] how to randomize data matrix
A - array(1:16, dim=c(4,4)) dimnames(A) - list(LETTERS[1:4], letters[1:4]) A[sample(1:4), ] A - array(1:16, dim=c(4,4)) dimnames(A) - list(LETTERS[1:4], letters[1:4]) A[sample(1:4), ] a b c d C 3 7 11 15 B 2 6 10 14 D 4 8 12 16 A 1 5 9 13 hope this helps. spencer graves [EMAIL PROTECTED] wrote: Dear R users: Is there a function or easier way to randomize the data between rows (considering a row as a whole unit)? For example, original data: A1 A2 A3 A4 B1 1 2 3 4 B2 5 6 7 8 B3 9 10 11 12 B4 13 14 15 16 randomized data: A1 A2 A3 A4 B4 13 14 15 16 B2 5 6 7 8 B1 1 2 3 4 B3 9 10 11 12 Thank you for your attention! Joshua __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] mtext / expression and font type of bold
mtext does not appear to be rendering a 'bold' expression. Is there another parameter to set? Thx. example (does not create bold (font=2) on plot) mtext( font=2, expression(paste(y, = , x + z), side=3 ) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] nls minFactor and constraints [was (no subject)]
In my experience, transformations of the type Doug just described has often made sums of squares (or log(likelihood)) contours more parabolic, thereby increasing the accuracy of the simple normal approximations to the distributions of parameter estimates. It is wise to check these things, as it is not always true. hope this helps. spencer graves Douglas Bates wrote: giovanni caggiano [EMAIL PROTECTED] writes: A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default one, 1/1024=0.000976563. Is there any way of setting the new minfactor to a lower level? You need to set control=nls.control(minFactor=1/4096) in the call to nls. 2. Is it possible to set some constraints upon the parameters to be estimated in a nls regression? Other than by parameter transformation, no. See section 3.4.1 of Bates and Watts (1988), Nonlinear Regression Analysis and Its Applications, Wiley to see how to use parameter transformations for this. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
