similar to: 2 post-doctoral positions in neurophysiological data analysis with R

Guys, I'm using a Linux PC (Pentium IV, Mandrake 10.1) and I've just tried to compile the new R-2.1.0 release with both gcc/g77 (3.4.1) and icc/ifort (8.1). Of course everything went fine with the GNU compilers. After checking the archives of the mailing list I tried compiling with the Intel compilers using the following options: CFLAGS = '-O2 -mp -prec_div' CXXFLAGS =

Hi all, I've uploaded STAR (Spike Train Analysis with R) on CRAN two days ago. The package is designed to analyze neuronal spike (action potential) trains. It uses S3 classes and methods and makes heavy use of other CRAN packages like gss, R2HTML, mgcv, survival. * Analysis of both spontaneous and stimulus evoked activity is implemented for single neuron spike trains as well as for many

Hi all, I've uploaded STAR (Spike Train Analysis with R) on CRAN two days ago. The package is designed to analyze neuronal spike (action potential) trains. It uses S3 classes and methods and makes heavy use of other CRAN packages like gss, R2HTML, mgcv, survival. * Analysis of both spontaneous and stimulus evoked activity is implemented for single neuron spike trains as well as for many

Hi all, The new version of STAR (0.2-2) is now available on CRAN. * An error in function varianceTime has been corrected (thanks to Chong Gu). * The vignette has been updated. * A new vignette is available on STAR web sire: http://sites.google.com/site/spiketrainanalysiswithr/ * The new goodness-of-fit test for spike train models announced in the previous release in now fully functional

Hi all, The new version of STAR (0.2-2) is now available on CRAN. * An error in function varianceTime has been corrected (thanks to Chong Gu). * The vignette has been updated. * A new vignette is available on STAR web sire: http://sites.google.com/site/spiketrainanalysiswithr/ * The new goodness-of-fit test for spike train models announced in the previous release in now fully functional

Hello everyone, I'm working on a package using S4 classes and methods and I ran into the following "problem" when I tried to create an "apply" method for objects of one of my new classes. I've found a way around the problem but I wonder if I did not paint myself into the corner. I'd like your opinion about that. So I have an object "myObj" of class

Hi, There is something I don't get with object of class "mle" returned by a function I wrote. More precisely it's about the behaviour of method "confint" and "profile" applied to these object. I've written a short function (see below) whose arguments are: 1) A univariate sample (arising from a gamma, log-normal or whatever). 2) A character string

am I right in the assumption, that for calculation of the condition numbers I have to use the correlation matrix of X, and not t(x) %*% x? > e <- eigen(t(x) %*% x) better (x must not have a first column of ones): > e <- eigen(cor(x)) > e$val [1] 6.6653e+07 2.0907e+05 1.0536e+05 1.8040e+04 2.4557e+01 2.0151e+00 > sqrt(e$val[1]/e$val) [1] 1.000 17.855 25.153 60.785 1647.478

I want to migrate my R workspace databases (e.g., .Rdata) from Windows to Linux. The R help file for "save" says that "[a]ll R platforms use the XDR representation of binary objects in binary save-d files, and these are portable across all R platforms." Is it is simple as that? Copy the Windows .Rdata file to the Linux .ext3 file system? Thanks, Derek Derek N. Eder

Sorry, I am sure, this must be documented somewhere (but there are that many docs and tutorials to scan for topics..., actually a great thing... but if you are in a hurry..): I want to save a plot as .ps (or .eps): > postscript("plot1.eps", horizontal=FALSE, onefile=FALSE,height=8,width=8,pointsize=10) > plot(hpfit$fit,rstudent(hpfit),xlab="Fitted

Hi all, I am wondering if anyone has implemented (or at least tried to) an automatic reparametrization in order to satisfy "trivial" constraints (in the sense of Dennis & Schnabel, 1983) in optimization problems. To be perhaps clearer let us consider a simple bi-exponential model for some recorded signal (sorry for the LaTex notations I hope they aren't too confusing): $s(t) = A

I am having trouble understanding what must be a quite simple rule of scope. In the code example below, the argument to the main function, my.subset, would like to be passed to the function LME. This does not happen however. Curiously, the other argument (my.data) is passed to LME. This problem goes away with this: assign("my.subset", my.subset, env = sys.frame()). It works, but it

Dear R-users, dear Prof. Ripley as package maintainer I tried to investigate the odd error, when I call nnet together with a 'weights' parameter, using the 'fgl' example in V&R p 348 The error I get is: Error in eval(expr, envir, enclos) : Object "w" not found I think it is a kind of scoping problem, but I really cannot see, what the problem exactly is. and

Dear R-users I use nnet for a classification (2 classes) problem. I use the code CVnn1, CVnn2 as described in V&R. The thing I changed to the code is: I define the (class) weight for each observation in each cv 'bag' and give the vector of weights as parameter of nnet(..weights = weight.vector...) Unfortunately I get an error during some (but not all!) inner-fold cv runs:

Isn't there a cryptic footnote somewhere in the blue book that describes regular expressions as "a funny little language ..." ? Well, I'm not laughing! I've googled and Man paged, but the GREP-style solution to the following problem still eludes me: ... Using a regular expression in the "pattern" argument to list.files() to restrict the return to filenames which

Christoph -- There was just a thread on this earlier this week. You can search in the archives for the title: "refitting lm() with same x, different y". (Actually, it doesn't turn up in the R site search yet, at least for me. But if you just go to the archive of recent messages, available through CRAN, you can search on refitting and find it. The original post was from William

I am just about working through Faraways excellent tutorial "practical regression and ANOVA using R" on page 24 he makes the x matrix: x <- cbind(1,gala[,-c(1,2)]) how can I understand this gala[,-c(1,2)])... I couldn't find an explanation of such "c-like" abbreviations anywhere. thanks for a hint. another problem: I couldn't load the faraway library, using the

How is exact pattern matching achieved in GREP (and GREPlike) functions ? # Want: listing of all object names that end in *.lm > objects(pattern="*.lm",pos=1) # ... but get: all objects that partially match *.lm, e.g., *.lme [1] "j3.lm" "J3.lme" "j8.lm" "J8.lme" # Want: position of string "4jan2002" in vector >

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

Hello, I am looking for documentation (PDF ?) about doing clustering with the EM Algorithm on R... I'm sorry for this question which may be trivial... Thanks... Dominique