similar to: Simulation functions for underdispered Poisson and binomial distributions

Dear all Somebody may have asked this before but I could not find any answers in the web so let me ask a question on lme. When I have a fixed factor of, say, three levels (A, B, C), in which each level has different size (i.e. no. of observations; e.g. A>B>C). When I run an lme model, I get the same degree of freedom for all the contrast t-tests (e.g. AvsB or BvsC). I have tried this to

Dear R users I would like to ask a question regarding to icc (intraclass correlation) or many biologists refer it to as repeatability. It is very useful to get icc for many reasons and it is easy to do so from linear mixed-effects models and many packages like psy, psychometric, aod and irr have functions to calculate icc. icc = between-group variance/(between-group variance + residual

Hello, I am using rbetabinom ( to generate beta binomial random variables) function available in the "emdbook"package written by Professor. Ben Bolker for my research study. I have no questions with this function. However, I am looking for the theoretical method/algorithm of the function "rbetabinom " . Morris (1997), American Naturalist 150:299-327 is given as the reference

I tried rsync 2.6.1cvs on my FreeBSD 4.X boxes. It dumps core when preserve_hard_links and backup. And SUPPORT_HARD_LINKS is true. rsync -avH --delete --backup --backup-dir=/some/backup/dir \ srchost::dir/ dir/ The core says... ------------------------------------------------------------------------ Program terminated with signal 11, Segmentation fault. #0 0x80536c0 in keep_backup

double-colon mode doesn't work in CVS version. -vv says port number is 0. % rsync -vv host.domain::any opening tcp connection to host.domain port 0 rsync: failed to connect to host.domain: Can't assign requested address (49) rsync error: error in socket IO (code 10) at clientserver.c(94) And --port=873 cannot be used in client mode now. I made a small sample patch. (Sorry, I

Dear R users, Recent changes to the MuMIn package now means that the model averaging command (model.avg) no longer returns confidence intervals, but instead returns zvalues and corresponding pvalues for fixed effects included in models. Previously I have used this package for model selection/averaging following Greuber et al (2011) where it suggests that one should use confidence intervals from

Hi all, I am currently doing a consistency analysis using an lmer model and trying to use parametric bootstrapping for the confidence intervals. My model is like this: model<-lmer(y~A+B+(1|C/D)+(1|E),binomial) where E is the individual level for consistency analysis, A-D are other fixed and random effects that I have to control for. Following Nakagawa and Scheilzeth I can work out the

Hello, Anyone who knows a fast and accurate algorithm for generating draws from an underdispersed Poisson distribution. Or even better, if there is a package containing such an implementation. Thanks Rene

Does anyone have R functions or library to fit a beta-binomial distribution with glm? Thanks.

Hi! As discussed in the thread "Question regarding patch for ProxyCommand setting". The patch is rather straight forward; maybe it would be a good idea to improve it in a way that it uses a list of string options that may have a "none" value to reset it to NULL. Ciao Thomas -------------- next part -------------- Index: readconf.c

Actually, what I do also propogates deletions. Since someone may unpack a tar containing files with earlier mtimes than a marker file, a simple --newer won't do it for us, either. Instead, I generate a list of all items, consisting of name and type, to which i append number of links, size, and mtime for files; link destination for symlinks; and for directories, fifos, chars, blocks,

I have just uploaded a new snapshot to http://www.mindrot.org/misc/openssh/ Snapshot production is now automated - new snapshots will be made at about 4:30 am (Australian Eastern time) and will be available from the URL above. This snapshot consists of mainly minor fixes over the previous. The race when sshd exits which was causing data loss (as evidenced by "ssh localhost dd

Dear R users: I am using lmer fo fit binomial data with a probit link function: > fer_lmer_PQL<-lmer(fer ~ gae + ctipo + (1|perm) -1, + family = binomial(link="probit"), + method = 'PQL', + data = FERTILIDAD, + msVerbose= True) The output look like this: > fer_lmer_PQL Generalized linear mixed model fit

I have data consisting of binary responses from a large number of subjects on seven similar items. I have been using lmer with (crossed) random effects for subject and item. These effects are almost always (in the case of subject, always) significant additions to the model, testing this with anova. Including them also increases the Somers' Dxy value substantially. Even without those

A package I have written makes considerable use of external C code. There appear to be no problems building a Windows binary with the GNU C compiler, but now I would like to make the package available for other platforms. A stringent check of the code with the gcc options '-Wall -pedantic' flags many nested functions and variable-length arrays that are not allowed in ISO C. Is it

The documentation states : An alternative parametrization (often used in ecology) is by the mean ?mu?, and ?size?, the dispersion parameter. However, this fails : > rnbinom(10, mu = 100, size = 0) [1] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Warning message: In rnbinom(10, mu = 100, size = 0) : NAs produced For dispersion set to 0, it should work like drawing from a Poisson distribution.

Hi, I am trying to connect points on a graph that originate from *different columns of data*. For each sample I have minimum and maximum data points and I would like to draw a line connecting these in order to visualize the spread, as well as where each sample is in relation to the x-axis. So far I can generate the points, but the only lines I have been able to make join all the minimum values

Dear All I'm logging the stdout and stderr of an R program into two separate files (stderr.txt and stdout.txt) using sink() I would like to append extra information such as "date", "memory usage" etc to every line of output that goes to stdout or stderr. For example > cat("hello \n") should give output that looks something like: "hello --- Thu Jun 19

Why is 19 March, 1947 a little longer than one day? x <- as.POSIXct("1947-04-16") julian(x, origin = as.POSIXct("1947-03-20")) Time difference of 27 days julian(x, origin = as.POSIXct("1947-03-19")) Time difference of 28.04167 days > julian(x, origin = as.POSIXct("1947-03-18")) Time difference of 29.04167 days I am running R-1.7.1 compiled on

I have just used the RAqua.pkg to install R, and it doesn't work! I have Mac OS X 10.3, and the old version of R works OK, but the .pkg thing installed, and then when I double-click on the "StartR" application nothing happens. Nothing at all, no little icon bobbing up and down in the dock, just nothing. What have I done wrong? I didn't have to install the other packages