search for: gibb

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 way my problem is pri...

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]         netbios name = PTA-CLUSTER         realm = AD.GIBB.CO.ZA         server string = Pretoria Cluste...

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 GIBB\nprice:*:100110...

...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, connecting as a gibb.local > user does work) > > getent passwd returns expected results, as does wbinfo -u > > # Global parameters > [global] >         netbios name = PTA-CLUSTER >         realm = AD.GIBB.CO...

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 "met_gaussian" updates the whole state with Metropolis method using independent Gaussian proposal distri...

...ote: (.. 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 > migration. Two questions about this, is 'gibb.local' the workgroup > name, if so, why does it have a dot in it ? Secondly, you mentioned > 'migrate', do you mean you migrated 'gibb.local' (a PDC domain) to the >...

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 fun...

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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 ideas why I am getting this warning and how I can fix it? -- View this message in context:...

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]<-...

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,...

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),        Trace("theta[1]") )   Error: could not find function "Sampler"   Is there anything else I need to download.   Thanks,     Jim L....

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 /usr/include/R_ext/Utils.h:27, from gibbs.c:7: /usr/include/R_ext/Boolean.h:29: conflicting types for `FALSE' /usr/include/Rmath.h:175: previous declar...

...ma is a var-covar matrix (however, it is NOT a correlation matrix). Thanks a lot! Dimitri function (n, mean = rep(0, nrow(sigma)), sigma = diag(length(mean)), lower = rep(-Inf, length = length(mean)), upper = rep(Inf, length = length(mean)), algorithm = c("rejection", "gibbs", "gibbsR"), ...) { algorithm <- match.arg(algorithm) cargs <- checkTmvArgs(mean, sigma, lower, upper) mean <- cargs$mean sigma <- cargs$sigma lower <- cargs$lower upper <- cargs$upper if (n < 1 || !is.numeric(n) || n != as.in...

...o share their work, or at least their insights. My data come with three complications: 1.. I do not have response values for all the sites within my study area. In order to evaluate the autocovariate term, I therefore need to be able to simulate the response value at unsurveyed sites with a Gibbs sampler or modified Gibbs sampler, as described in Augustin et al. 1996 (Journal of Applied Ecology 33: 339-347) and 1998 (Environmetrics 9: 175-196). 2.. My study area amounts to continental Africa South of 6 degree North; both response and environmental data have a spatial resolution of 0.5 d...

...o 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 the Generalised Linear Mixed Model by Gibbs Sampling (using the Bayesian paradigm). The basic idea is that one declares a particular factor to be a random effect with one statement and then performs the Gibbs sampling with another statement with syntax somewhat lik...