Displaying 20 results from an estimated 4000 matches similar to: "possible bugs: boundary conditions and random distribution parameters"
2001 Dec 17
1
behavior of r* and d* functions at boundaries (PR#1218)
(Sent this to r-help back in October, got no comments, forgot
to re-submit it as a bug report.)
There are a few inconsistencies, at least, in some of the functions that
generate random deviates from particular distributions (I think they're
bugs because they're inconvenient, but maybe someone can make an argument
for the current behavior). If people think these are really bugs I can
1997 Dec 13
1
R-beta: Compile error; R-0.60.1, Solaris 2.6, gcc 2.7.2.1
Hi!
I have just downloaded the R-0.60.1 sources and have problems compiling R
on a Sun Ultra 1 running Solaris 2.6 and gcc 2.7.2.1.
I have not been able to find to find any compiling hints in the
documentation or the FAQ.
After ./configure I use make and get the output below.
Any hints are welcome.
I am not on the list, so please answer me directly too.
Best regards
Jens
---
Jens Lund
2009 Mar 17
3
R does not compile any more on FreeBSD 8.0-CURRENT
On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks
with the following messages:
----------------------------------------------------------------------
[...snip...]
gcc -std=gnu99 -I. -I../../src/include -I../../src/include
-I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o
gcc -std=gnu99 -I. -I../../src/include -I../../src/include
-I/usr/local/include
2002 Mar 12
1
using R API in dynamically loaded code?
I'm probably missing something very basic here, but:
I've written some C code that I load into R dynamically. In the course
of this C code, I generate some multinomial random deviates. I initially
used the publically available "randlib" library, which also implements
its own random number generator and binomial deviates (which are used to
generate the multinomial deviates).
1999 Nov 22
0
No subject
This is off-topic (apologies), but I thought I might get a lead or two
here.
I'm interested in generating random deviates from a multivariate
distribution which is a generalization of the beta distribution -- the
Bayesian canonical distribution for the parameter estimates of a
multinomial distribution. Given a vector (length n-1) of probabilities p
and a vector (length n) of shape
1999 May 03
1
problems compiling R-0.63.3 on alpha
Hi again !
Thanks for the info on updating the config.site file which I
have done. I have also added -lm in the Makeconf manually
because this is needed explicitly for DEC cc.
However, there are still a few problems when linking some
of the files as you can see from the enclosed log.
Ciao,
Andreas
-------------------------------------------------------
R-0.63.3>make
make[1]: Entering
1998 Nov 06
1
DEC alpha INSTALLATION R-0.62.4
Hi,
Just downloaded the R-0.62.4 of R and tried to install it. With the
standard procedure :
./configure
make
At the end of the compilation I got the following message :
ld:
../lib/libunix.a(system.o): main: multiply defined
fort: Severe: Failed while trying to link.
*** Exit 1
Stop.
*** Exit 1
Stop.
*** Exit 1
Stop.
*** Exit 1
Stop.
I attach the printout after the ./configure and make
2001 Sep 20
0
3d java etc.
There was some interest in the commands for creating an HTML file of
3D graphics that can be shown with a Java applet.
Looking at things I discovered (of course) that I should really clean up
quite a few things before releasing it for real. I hope to do some of
that this weekend.
In the meanwhile, here are a couple of pointers to the Java applet &
documentation (apparently free for
2002 Feb 13
0
glmms with negative binomial responses
I am trying to find a way to analyze a "simple" mixed model with two
levels of a treatment, a random blocking factor, and (wait for it)
negative binomial count distributions as the response variable. As far as
I can tell, the currently available R offerings (glmmGibbs, glmmPQL in
MASS, and Jim Lindsey's glmm code) aren't quite up to this. From what I
have read (e.g.
1999 Oct 18
1
memory efficiency in R
I'm trying to answer a question from a student about memory use in R
(I won't go into the details right here).
I have a really vague memory of having read a document, possibly by
Venables or Ripley, discussing the awfulness of memory allocation in
S-PLUS, and giving (in the context of a bootstrapping analysis of shoe
size data??) some general strategies for conserving memory in S-PLUS.
2001 May 16
0
glm.nb difficulties
I'm having problems (or to be precise a student is having problems,
which I'm having problems helping her with) trying to use glm.nb() from
the MASS package to do some negative binomial fits on a data set that is,
admittedly, wildly overdispersed (some zeros and some numbers in the
hundreds).
glm.nb is failing to converge, and furthermore is (to my surprise)
producing values of theta
2000 Feb 29
0
R-1.0.0
I want to add my two cents of congratulation to the R core team.
I also want to encourage everyone who uses R to be an active, not a
passive user -- the fastest way R will get better is if the folks who use
it submit bug reports, suggestions, R code for their particular fields,
documentation, even patches and code fixes. R is big and complicated
enough now that we can't leave testing to
1999 Dec 09
0
setting par(fig) resets par(mfrow), par(mfcol)
Can we add a note to the documentation that setting par(fig) resets
par(mfrow) and par(mfcol) to c(1,1)?
Or are mfrow and mfcol now deprecated in favor of all the split screen
stuff? (I was spending the morning trying to write some code that plotted
multiple subplots within whatever plot region was active at the moment; I
was able to set and reset fig successfully, but got very confused as to
2003 Mar 04
1
CRAN scripts?
For various reasons, I've opted to make my packages available from my
own web page rather than submitting them to CRAN (mostly laziness -- for
a long time I didn't have the packages quite cleaned up enough to pass all
the tests). It occurred to me to wonder about the scripts used by CRAN
maintainers to generate the PACKAGES file, and to generate PACKAGES.html
from PACKAGES. Are
2000 Sep 26
1
weights in nls
Does the nls package actually allow for weighted nonlinear regression?
(i.e., I have data with individual variances associated, I'd like to use
1/var to weight the points.) The "nls" function does have a weights
argument, but it doesn't seem to do anything as far as I can tell ...
thanks ...
Ben Bolker
--
318 Carr Hall bolker at
2002 Nov 26
0
nlme: gnls with weights and correlation arguments
Some students of mine are trying to use gnls, the generalized non-linear
least squares function within the nlme library, to study evolutionary
questions where correlations between traits at the species level are
non-independent because of the evolutionary relatedness of the species.
Specifically, they're using a non-linear function (log(sexual dimorphism)
~ log(a + b*variation in mating
1999 May 03
0
compilation of R-0.63.3 on alpha (PR#183)
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Hi !
I have problems compiling R successfully on a DEC-UINX 4.0E.
I have applied the recommended config.site, which I enclose.
As can be seen from the compilation log there are linking errors...
I did a 'make check' which fails for the R
2005 Nov 07
0
Brainstorm: Alpha and Beta testing of R versions
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
2000 Oct 20
1
Linux -> Win2K file transfer
Just a quick question, in case I'm doing something really boneheaded
that could be easily sorted out.
I'm attempting to save() datasets on Linux (R 1.1.1) and load() them on
Win2K (rw1011, fetched from CRAN today). I get the "restore file
corrupted" message every time. I've tried saving with ascii=TRUE and
FALSE, and the ASCII versions look OK (it's my impression
2003 Jan 27
1
help page for anova.glm/variation between S-PLUS and R behavior
When using test="F" in stat.anova() / anova.glm(), R uses the assumed
dispersion parameter for the specified family (e.g. scale=1 for binomial),
while S-PLUS automatically uses the estimated dispersion parameter
(residual deviance/residual df). I think there are good reasons for the
behavior in R -- it fits with the "you get what you actually asked for"
philosophy -- and