similar to: Failure to run mcsamp() in package arm

Hi, I have the following piece of code that is part of a larger function. This piece is the most time consuming part of the function, and I would like to make this a bit more efficient. Could anyone suggest a way to do this faster? In particular, I would like to replace the nested "for" loop with a faster construct. I tried things like "kronecker" and "outer"

I am moving this to r-devel. The problem and solution below posted on r-help could have been a bit slicker if %*% worked with multidimensional arrays multiplying them so that if the first arg is a multidimensional array it is mulitplied along the last dimension (and first dimension for the second arg). Then one could have written: Tbar <- tarray %*% t(wt) / rep(wti, each = 9) which is a bit

I have written a function called mcsamp() that is a wrapper that runs mcmcsamp() and automatically monitors convergence and structures the inferences into vectors and arrays as appropriate. But I have run into a very little problem, which is that mcmcsamp() shortens the variable names. For example: > set.seed (1) > group <- rep (1:5,10) > a <- rnorm (5,-3,3) > y <-

Version 0.9975-11 of the lme4 package has been uploaded to CRAN. The source package should be available on the mirrors in a day or two and binary packages should follow soon after. There are several changes in this release of the package. The most important is the availability of a development version of lmer called, for the time being, lmer2. At present lmer2 only fits linear mixed models.

Version 0.9975-11 of the lme4 package has been uploaded to CRAN. The source package should be available on the mirrors in a day or two and binary packages should follow soon after. There are several changes in this release of the package. The most important is the availability of a development version of lmer called, for the time being, lmer2. At present lmer2 only fits linear mixed models.

Dear R-Users: I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works in lmer2 to get the robust estimates of

Hello, I am using odesolve to simulate a group of people moving through time and transmitting infections to one another. In Matlab, there is a NonNegative option which tells the Matlab solver to keep the vector elements of the ODE solution non-negative at all times. What is the right way to do this in R? Thanks, Jeremy P.S., Below is a simplified version of the code I use to try to do this,

Hi All, I have a user who is receiving this error after running the following: library(rjags) library(R2jags) x = c(1.6907, 1.7242, 1.7552, 1.7842, 1.8113, 1.8369, 1.8610, 1.8839) n = c(59, 60, 62, 56, 63, 59, 62, 60) r = c(6, 13, 18, 28, 52, 53, 61, 60) N = 8 data=list("x","n","r","N") inits=function(){ list(alpha.star=0,beta=0) }

> (fm1 <- lmer2(Reaction ~ Days + (Days|Subject), sleepstudy)) Error in as.double(start) : Calloc could not allocate (888475968 of 4) memory ************************* > sessionInfo() R version 2.4.1 (2006-12-18) powerpc-apple-darwin8.8.0 locale: C attached base packages: [1] "grid" "datasets" "stats" "graphics" "grDevices"

I seem to come to this problem alot, and I can find my way out of it with a loop, but I wish, and wonder if there is a better way. Here's an example (lmer1-5 are a series of lmer objects): bs=data.frame(bic=BIC(lmer1,lmer2,lmer3,lmer4,lmer5)$BIC) rownames(bs)=c('lmer1','lmer2','lmer3','lmer4','lmer5') best=rownames(bs)[bs==min(bs)] > best [1]

Hi All: I had a basic question to ask. I am running R2WinBUGS so that I could automate the running of my model using 1000 simulated datasets. Below is the code I am using. The only problem I am having is the bugs output that comes out shows my parameters as nos with 1 decimal place after. I would want to have the parameters with 5 places after decimal. How would I specify that in my code for

Dear members, I would like to switch from nlme to lme4 and try to translate some of my models that worked fine with lme. I have problems with the pdMat classes. Below a toy dataset with a fixed effect F and a random effect R. I gave also 2 similar lme models. The one containing pdLogChol (lme1) is easy to translate (as it is an explicit notation of the default model) The more parsimonious

Hello Samba Team, I am new to Linux, but not to networking. However, I am having a bear of a time setting up Samba on a small test network - 3 Machines. I have read all your example setup files for Samba, config, lmhosts, hosts, resolve, etc., and have read back to back "Linux - Samba Server Administration" by Roderick W. Smith (Craig Hunt Linux Library) My test network (10-100

Hello EVERYONE, I need an URGENT help from you please! How can I see the "estfun" (empirical estimating function) and "df" (degree of freedom) from the following mixed-model please? (fm1 <- lmer2(Reaction ~ Days + (Days|Subject), sleepstudy)) Many thanks in advance for your kind help. Sattar

Dear all, I want to estimate a crossed-random-effects model (i.e., measurements, students, schools) where students migrate between schools over time. I'm interested in the fixed effects of "SES", "age" and their interaction on "read" (reading achievement) while accounting for the sample design. Based on a previous post, I'm specifying my model as: fm1 <-

Hi all, 2 days ago, managed to install rhat and asterisk, starting with 2 sip phones, simple config. CLI reports : "playing 'vm-theperson' (language 'no')" when transferred to voicemail after timeout, or "playing 'vm-password' (language 'no')" when dialing into voicemail extension. But, no sound, nothing heard in phones. First time, first

Is anyone using Webmin with CentOS? I've always found it works very well with RHat Linux. I've not used RHEL so I'm not sure. I know on my SuSE server it doesn't seem to work well and suspect there are some location problems. -- <<JAV>>

Hello R list, I am hoping to conduct a logistic regression with repeated measures, and would love an actual "code run through" for such an analysis. I found only one related post on this list, but a full answer was never provided. I understand that the routine lmer (or lmer2) in the lme4 package is often recommended in such a case, but actually implementing it is where I've hit a

This is more of a pam question then a samba question, but I thought I'd start here and see if I can get an answer. I've gotten pam_winbind.so working with gdm (on RHAT 8) using the following /etc/pam.d/gdm file. I've put + signs to show the lines I added I added to the stock RHAT 8 gdm pam def.: #%PAM-1.0 + auth sufficient /lib/security/pam_winbind.so + auth

Hi, we have installed ocfs2 on Rhat 4. It is being used as a general clustered file system. There are no oracle binaries or datafiles on the ocfs volume. So no need for RMAN or oarcle agents etc etc. The customer would like to backup the volume using arcserve. However CA are saying that they cannot backup from an ocfs volume. Has anyone out there got any words of wisdom about backing up