search for: gibbe

Hello, thank you very much for your previous answers about the C++ code. I am interested in the application of the Gibbs Sampler in the IRT models, so in the function MCMCirt1d and MCMCirtkd. I've found the C++ source codes, as you suggested, but I cannot find anything about the Gibbs Sampler. All the files are for the Metropolis algorithm. Maybe I am not able to read them very well, by the

On 2019/04/25 14:44, Rowland Penny via samba wrote: > OK, post your smb.conf Thanks for help.... remember this has been working up to now and only a few users have the password prompt..  (btw "gibb.local" is a trusted samba3 domain used for migration, connecting as a gibb.local user does work) getent passwd returns expected results, as does wbinfo -u # Global parameters [global]

Domain member server (Debian stretch with 4.8 from the Van Belle repo) getent passwd| grep nprice GIBB\nprice:*:1001104:1000513::/home/GIBB/nprice:/bin/false getent passwd GIBB\\nprice (returns nothing) getent passwd 1001104 also returns nothing wbinfo -u works fine wbinfo --uid-info 1001104 GIBB\nprice:*:1001104:1000513::/home/GIBB/nprice:/bin/false wbinfo -i GIBB\\nprice

On Thu, 25 Apr 2019 15:39:21 +0200 Neil Price via samba <samba at lists.samba.org> wrote: > On 2019/04/25 14:44, Rowland Penny via samba wrote: > > OK, post your smb.conf > > Thanks for help.... remember this has been working up to now and only > a few users have the password prompt..  (btw "gibb.local" is a > trusted samba3 domain used for migration,

On 2019/04/25 13:46, Rowland Penny via samba wrote: > No, the key error is that dns doesn't seem to be working, if you can > connect via ipaddress, then you are not using kerberos. > The server is resolved just fine, it just gets a password prompt. The server can also resolve the client correctly. I see this issue came up before

Hi R Users: This package provides two generic functions for performing Markov chain sampling in a naive way for a user-defined target distribution, which involves only continuous variables. The function "gibbs_met" performs Gibbs sampling with each 1-dimensional distribution sampled with Metropolis update using Gaussian proposal distribution centered at the previous state. The function

On 2019/04/25 16:24, Rowland Penny via samba wrote: (.. lots of helpful stuff) Thanks for advice on smb.conf.. Today people who could not access it yesterday can, and some people who could access it can't and even one who cannot access it via the ip address, so you know what I'll be doing this weekend. > You said above that 'gibb.local' is a trusted domain that was used for

I suspect it''s probably not a good idea but I was wondering if someone could clarify the details. I have 4 250G SATA(150) disks and 1 250G PATA(133) disk. Would it cause problems if I created a raidz1 pool across all 5 drives? I know the PATA drive is slower so would it slow the access across the whole pool or just when accessing that disk? Thanks for your input. - Chris

Dear all: I am using R to do multiple imputation for longitudinal data set. The Gibbs chain basically requires draw posterior distribution of model parameters, including the random effects. The multiple imputation requires several independent Gibbs chains. So my program structure is like: for (chain in 1:5) { # perform Gibbs sampling... for (row in 1:row.no) { b.row=some function # draw

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I have been using the rtmvt function in the {tmvtnorm} package i'm getting the warning: "Acceptance rate is very low and rejection sampling becomes inefficient. Consider using Gibbs sampling." but i AM specifying the gibbs algorithm!!: rtmvt(M, mean=q[,,i,j], sigma=((u[i,j] + nu[i])/(p+nu[i]))*delta[,,i], df=ceiling(nu[i]+p), lower=c(0,0), algorithm="gibbs") Any

I have the following code, gibbs <-function(m,theta = 0.25, lambda =0.55, n =1){ alpha <- 1.5 beta <- 1.5 gamma <- 1.5 x<- array(0,c(m+1, 3)) x[1,1] <- theta x[1,2] <- lambda x[1,3]<- n for(t in 2:(m+1)){ x[t,1] <- rbinom(1, x[t-1,3], x[t-1,1]) x[t,2]<-rbeta(1, x[t-1,1] + alpha, x[t-1,3] - x[t-1,1] + beta) x[t,3]

I am writing a Gibbs sampler. I think it is outputting some of what I want, in that I am getting vector of several thousand values (but not 10,000) in a txt file at the end. My question is, is the error message (see below) telling me that it can't output 10,000 values (draws) because of a limitation in my memory, file size, shape etc, or that there is an error in the sampler itself? >

Hey everyone, I have read the paper by Ritter and Tanner(1992) on Griddy-Gibbs sampler and I am trying to implement it in R without much luck. I was wondering if anyone had used this or could point me to any example code. Thanks, Liz --------------------------------- [[alternative HTML version deleted]]

hi i'm looking for a gibbs sampling algorithm for R for the case of mixture of K normals, and in particular for the case of bivariate normals. i'd be grateful if anyone could send its own R-routine, at least for the univariate case. thank you in advance matteo

I have downloaded the Umacs (Universal Markov chain sampler) and submitted the following sample code from Kerman and Gelman.   s <-Sampler( J=8, sigma.y  =c(15,10,16,11,9,11,10,18),           y  =c(28, 8,-3,7,-1,1,18,12),      theta =Gibbs(theta.update,theta.init),           V =Gibbs(V.update,mu.init),         mu =Gibbs(mu.update,mu.init),         tau =Gibbs(tau.update,tau.init),       

Hi, I want to use R_qsort_int_I() in my C function, but getting the following error. It looks like there is a conflict between Rmath.h, which I use to generate random numbers, and R_ext/Boolean.h I would appreciate any help to fix this problem. gcc -ansi -g -o Gibbs gibbs.c subroutines.o rand.o vector.o -lm -lRmath -llapack -lblas -lfrtbegin -lg2c -lm -shared-libgcc In file included from

Hello! I was wondering if it's possible to see the actual code of checkTmvArgs function that is part of the code for rtmvnorm (which is below - I just typed "rtmvnorm" on the prompt). I get an error: Error in checkTmvArgs(mean, sigma, lower, upper) : sigma must be a symmetric matrix At the same time I am pretty sure that the matrix I am passing as sigma is a var-covar matrix

Hello everyone, I have some binary, spatially autocorrelated data I would like to run autologistic regression on. I hope to incorporate both ordinary covariates (environmental predictors) and a spatial autocovariate in the model, ideally with a second-order neighbourhood structure. Since my computing skills are limited, I am wondering if anyone has composed an algorithm for this purpose, and

Sort of a warning before I start: This post may be considered to describe a rather amateurish approach to distributing software which may annoy some people, but I sincerely hope it doesn't. I've been working for some years with David Clayton on a project which started life as an S package but has now turned into an R library. It is (now) called GLMMGibbs and estimates the parameters of