Dear all,
I'm new R's user and I'm looking for package dealling with Path analysis. Does it
exist ? Where ?
Best,
Regis Martin PhD Student
Laboratory of Altitutdinal Population Biology UMR CNRS 5553
Universté de Savoie
Bât. Belledonnes
00 33 (0)4 79 75 86 44
[EMAIL PROTECTED]
You are apparently fitting a series for which the selected order is zero,
and ar.burg is not designed to cope with that (and would in any case tell
you nothing useful). The default method does cope, from your output.
Why are you fitting an AR model to a series with apparently no
correlation?
A solution is at hand using the 'irts' (irreglar time-series)
class from package tseries.
If your raw data is in a csv file, you could proceed as follows:
mydata - read.csv(filename,header=TRUE)
basedate - as.POSIXct(strptime(2003-01-01 00:00:00,format=%Y-%m-%d %X))
rawdates -
Check out the 'sem' package by John Fox.
Marwan
===
Marwan Khawaja [EMAIL PROTECTED]
Associate Professor Director
http://webfaculty.aub.edu.lb/~mk36
Center for Research on Population Health
Faculty of Health Sciences
Bonjour,
J'ai téléchargé SciViews Insider que je trouve très convivial.
Par contre, je n'arrive pas à comprendre comment enregistrer un script R en type de
fichier R justement.
Mes programmes fonctionnent très bien, mais SciViews me propose uniquement de les
enregistrer au format txt sous un
Dear all,
I'm analyzing a binary outcome using glm() with a binomial distribution and
a logit link, and have now reached the point where I'd like to do some
model checking. Since my data are in binary form I'd like to collapse over
the cross-classification of the factors before the model
Please, use the mailing list language: English (or mail me directly).
(French version of the answer follows).
The question is: how to save a R script document in SciViews since the save
as... dialog box proposes only '.txt' files as allowed type.
Answer: you just have to append a '.R' extension
Dear Henric,
The following paper deals with goodness-of-fit test for sparse (and even
binary) data:
Kuss O. Global goodness-of-fit tests in logistic regression with sparse
data, Statist Med, 2002, 21:3789-3801.
It should not too hard to write code for some non-standard and (probably
under-used)
Thanks.
On Thu, 2003-06-19 at 01:52, Prof Brian Ripley wrote:
You are apparently fitting a series for which the selected order is zero,
and ar.burg is not designed to cope with that (and would in any case tell
you nothing useful). The default method does cope, from your output.
Why are
I'm running R 1.4.1 under linux , recently I installed the package
clines_1.0.tar.gz
R CMD INSTALL clines_1.0.tar.gz
and it is installed with no errors
when I try to use it , I get this error
library(clines)
Error in dyn.load(x, as.logical(local), as.logical(now)) :
unable to load shared
Hi All,
does anyone know if the package GLME by J. Pinheiro is available anywhere
in any form? checking on the archive I got that it was at some point, as as
a beta version (for S-Plus only, alas)...
Cheers,
Federico
=
Federico C.F. Calboli
Department of Biology
Greetings, R-Wizards:
Earlier this week I requested help with trying to find an extremum subject
to a nonlinear constraint. Many thanks to Martin Maechler, Spencer Graves,
and Jonathan Baron, who all suggested optim() rather than nlm(), and to
Robert Gentleman who suggested using a half-interval
I think your R is too old. Packages can indicate they need a particular
version of R, but it is unreasonable to expect them to be tested on
versions predating the package (which as clines is not on CRAN I can't
check but suspect to be the case).
On Thu, 19 Jun 2003, Karim Elsawy wrote:
I'm
On Fri, 20 Jun 2003, Masayoshi Hayashi wrote:
In MDI mode of Windows, is it possible to save window size and other
parameter settings of a graphics device when it is activated, much like
Rconsole file?
No, but you don't need to.
Size is part of the arguments of the windows() device, and you
On Thu, 19 Jun 2003, Prof Brian Ripley wrote:
I think your R is too old. Packages can indicate they need a particular
version of R, but it is unreasonable to expect them to be tested on
versions predating the package (which as clines is not on CRAN I can't
check but suspect to be the
Paul, David A wrote:
I've been using par() to check the graphics parameters
associated with both plot(fitted linear model) and
plot(grouped data object). AFAIK the only differences
are in the $cxy, $usr, $xaxp, and $yaxp parameters but
the background color for the grouped data plot is grey
while
I generated a PDF output file of 10 plots. When I try to view it with
Adobe reader (R4 R5), it will lockup the reader (it is consuming 100% of
the CPU) after presenting the 4th plot. I can generate the plots just fine
in Windows and as a postscript file reading it with GSview.
Is there anyway
Thank you both for pointing out that this is a lattice
plot (ie, R's version of Trellis graphics) and therefore
needs something other than par().
I was able to use IE6.0 to search for trellis and
find the relevant commands (after using help.start(),
of course). This brings up another question:
Paul, David A wrote:
I've been using par() to check the graphics parameters
associated with both plot(fitted linear model) and
plot(grouped data object). AFAIK the only differences
are in the $cxy, $usr, $xaxp, and $yaxp parameters but
the background color for the grouped data plot is
I too am interested in analysis of sparse data, and I couldn't find this
journal
easily, but I found an Oliver Kuss presentation that likely summarizes the
material. You can find that presentation here:
http://www.stats.gla.ac.uk/~goeran/euroworkshop/webpages/2002/slides/oliver.pdf
(Also,
Hello,
I have a simulated data structure in which students are nested within
teachers, and with each student are associated two test scores. There
are 20 classrooms and 25 students per classroom, for a total of 500
students and two scores per student. Here are the first 10 lines of
my dataframe
Federico Calboli [EMAIL PROTECTED] writes:
Hi All,
does anyone know if the package GLME by J. Pinheiro is available anywhere
in any form? checking on the archive I got that it was at some point, as as
a beta version (for S-Plus only, alas)...
Cheers,
Federico
I don't think it is
Paul, == Paul, David A [EMAIL PROTECTED] writes:
Is there a convenient way to decide whether or not the
generic plot( ) is going to use regular or trellis
plotting? I looked at methods(plot) and didn't find any
groupedData plot methods listed, so perhaps this is the
Is it possible in R to subset a dataframe by more than one factor, all at
once?
For instance, I have the dataframe:
data
p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 pred
10 1 0 0 0 0 0 0 0 0 0.5862069
40 0 0 0 0 0 0 0 0 1 0.5862069
50 0 0 0 0 0 1 0
Fernando Henrique Ferraz Pereira da Rosa wrote:
Is it possible in R to subset a dataframe by more than one factor, all at
once?
For instance, I have the dataframe:
data
p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 pred
10 1 0 0 0 0 0 0 0 0 0.5862069
40 0 0 0 0 0 0
I'd like to understand better how ordered and non-ordered factors are
treated differently when included as explanatory variables in statistical
models. Also, it appears as though glm [family=binomial] (base) treats
ordered factors differently than lrm (design). For example, when fitting
the same
Thanx to all who responded to my plea for help. You were right, I did not
have the Path environment set properly for the tools package. I get a
little further now, but still get an error message.
My Cmd Window looks like this:
Rcmd SHLIB combo.f
ar cr combo.a *.o
ranlib combo.a
Fernando Henrique Ferraz Pereira da Rosa [EMAIL PROTECTED] writes:
Is it possible in R to subset a dataframe by more than one factor, all at
once?
For instance, I have the dataframe:
data
p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 pred
10 1 0 0 0 0 0 0 0 0 0.5862069
When I attempt to build v.1.7.1 on a Darwin 6.6 system I get the following
failure when linking in src/main:
gcc -framework Carbon -mdynamic-no-pic -L/sw/lib -L/usr/local/lib -o R.bin
CConverters.o Rdynload.o RNG.o apply.o arithmetic.o apse.o array.o attrib.o
base.o bind.o builtin.o character.o
Hi all,
I am trying to model (continuous) spatial variation in a response variable
as a function of one or more of several explanatory variables. I am
principally interested in obtaining some measure of the relative
importance of the explanatory variables. I have found several R
libraries
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