similar to: nls: constraints (lower/upper) (PR#8401)

Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code below ... If I can I will try to hack the code, but I will probably start by redefining my function with

I appreciate Brian and Martin's answers -- and I certainly don't spend as much time & energy maintaining and answering questions about R as they do -- *but* it does seem to me that it would make a number of new (switching) user's lives easier if there were a succinct list of these differences, with a disclaimer ... I would be willing to maintain such a list, but since I

I'm very excited by the new mle package now incorporated in stats4. If possible, I'd like to help develop it. In the past I wrote a similar package (mleprof, available from http://www.zoo.ufl.edu/bolker/R/src), and would like to see if there's anything that my package does that I could contribute (in particular, I'd like to make sure that the code is as robust as possible in

I'm trying to do a simple (?) analysis of a 1D spatial data set, allowing for spatial autocorrelation. (Actually, I'm comparing expected vs. observed for a spatial model of a 1D spatial data set.) I'm using models like gls(obs~exp,correlation=corExp(form=~pos),data=data) or gls(obs~exp,correlation=corLin(form=~pos),data=data) This form is supposed to fit a linear model of

Just in case anyone cares or is hitting the same problem: to install current mgcv (1.0-5) on 1.9.0 on Knoppix/Debian unstable I had to: # cd /usr/lib # ln -s /usr/lib/atlas/libblas.so.3 libblas-3.so # ln -s /usr/lib/atlas/liblapack.so.3 liblapack-3.so Otherwise compilation couldn't find -lblas-3 or -llapack-3 (I could have gotten away with the links in /usr/lib/atlas instead of /usr/lib,

Not really a bug (I eventually discovered), but ... When running GaussRF()/DoSimulateRF() with n>1, the default pch="!" prints backspaces to the terminal, which causes problems (LaTeX barfs) if you're running this within an Sweave() job. Setting RFparameters(pch="") fixes the problem. Could put this in the documentation, but I don't know where you could

My most common problem with the bug reporting system is distinguishing between bugs and my own stupidity or confusion. So I post to the r-devel list to ask; even when there is a response, I may then fail to get around to submitting the bug report itself ... I know R-core doesn't want the bug list cluttered up with non-bugs, but this two-step process often gets in the way of my filing

I was sitting in the coffee room at work listening to people complain about a recent seminar about nanotechnology using the terms nanofluidics, nanofactory, nano-this, and nano-that ... I found myself thinking "well the speaker should just have said with(nano, ...) Un(?)fortunately there's no-one here I can share that thought with. -- 620B Bartram Hall

I was getting similar errors, which I finally tracked down to the following: I had accidentally left an extraneous "test.R" in my pkg/R directory; that file contained a system call to an external program that created a particular file, which I then tried to read into R. The R code that triggered the error from .tryQuietly was the attempt to open the file. I figured this out by

[redirected from R-devel: this really belongs on R-help] I have two sets of time-series that I imported from Excel using RODBC and placed in "securities" and "factors". What I need to do is generate t-scores for each security-factor pair. I tried the following: t1 <- t.test(securities[,3:42], factors[,2:41], var.equal=TRUE) ANSWER: If securities and factors

A student asked me if it was possible to draw boxplots where the boxes themselves were grouped: I was able to hack boxplot.formula() to do the right thing, more or less, by incorporating an argument (space) and some code from barplot. with the extended boxplot.formula() below, the following commands "do the right thing" (produce boxes grouped by levels of the second factor): r =

I'm trying to figure out the best way of fitting the same negative log-likelihood function to more than one set of data, using mle() from the stats4 package. Here's what I would have thought would work: -------------- library(stats4) ## simulate values r = rnorm(1000,mean=2) ## very basic neg. log likelihood function mll <- function(mu,logsigma) {

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

Tony Plate <tplate <at> acm.org> writes: > > Since the virtue and reliability of Wikis was brought up, I created a R > Wiki page for this at > http://www.sciviews.org/_rgui/wiki/doku.php?id=beginners:surprises:emptysetfuncs > > > Anyone: please correct errors and improve it! > > Tony Plate > OK, now I have another question: I see a wiki at

Tony Plate <tplate <at> acm.org> writes: > > Since the virtue and reliability of Wikis was brought up, I created a R > Wiki page for this at > http://www.sciviews.org/_rgui/wiki/doku.php?id=beginners:surprises:emptysetfuncs > > > Anyone: please correct errors and improve it! > > Tony Plate > OK, now I have another question: I see a wiki at

I have a package with some embedded legacy FORTRAN code (for computing complex Bessel functions, written in 2003 by C. Bond to implement the algorithms of Zhang and Jin 1996). It worked well until recently [despite warnings about deprecated headers "includes at least one deprecated or antiquated header" -- when I tried to fix these the code stopped working, so I left them alone]. Now an

OK: despite Dirk's very kind help, I decided that trying to deal with R configuration and Debian configuration simultaneously was too difficult. I did manage to solve my problem by reconfiguring/making/ installing all of 2.3.1 from source: ./configure F77=/usr/bin/g77 make make install A few questions inspired by this experience: (1) it seems a bit odd that R sets F77=gfortran by

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

I'm trying to build an RPM of R 2.3.1 on a very old RedHat system (specifically, a ROCKS 3.3.0 cluster which is built on RH enterprise 3 (I think??)) I downloaded R-2.3.1.tgz from CRAN; downloaded the R.spec file cran.r-project.org/http://cran.r-project.org/bin/linux/redhat/SRPMS/ ; and ran rpmbuild -ba R.specs. Everything goes along fine until ... make[5]: Entering directory

It surprised me that prod(numeric(0)) is 1. I guess if you say (operation(nothing) == identity element) this makes sense, but ?? Looking in the code, this makes sense: basically (s=1; for i=0 to length(x), multiply s by x[i]) -- which comes out to 1. What *should* prod(numeric(0)) produce? I couldn't find the answer documented anywhere. (And how about sum(numeric(0))==0, which for