similar to: Jags problem

Hi, anybody can help me with this? can JAGS solve the inverse of a matrix in the 3-way array? Thank you! for(i in 1:n){ for(a in 1:t[i]){ for(b in 1:t[i]){ sigma[i,a,b]<-pow(rho,t[a]-t[b]) } } sigmainverse[i,,]<-inverse(sigma[i,,]) # this is where jags got error } [[alternative HTML version deleted]]

Hallo! I want to use the package bayesmix. Trying the examples I had no success. The reason is, I think: > haveJAGS() [1] FALSE Have read of JAGS executable (I could not find JAGS.exe in my R directory). What is JAGS? Where can I find or download it? Karl

Dear all, I have a question regarding using JAGS and R. My problem is that every single time I want to call JAGS from R the latter crashes (i.e. it turns pale and the Windows tells me "R has stopped working". Strangely, if there is a mistake in my jags code, this will be reported without a crash. Only when the code is right and the model should start to run, R stops working. I already

I define priors in jags within r using a gamma distribution. I would like to control the shape but I have problems. Any help will be usefull. From help of dgamma ___________________ The Gamma distribution with parameters shape = a and scale = s has density f(x)= 1/(s^a Gamma(a)) x^(a-1) e^-(x/s) and rate=1/scale From jags user manual ____________________ dgamma(r, mu) has a density of

Anyone used jags.parallel in latest version of R2jags? Ubuntu Oneiric, just ran updates in R to get latest R2jags package which supposedly has added jags.parallel command to send chains to multiple cores ... but when I submit, I get: test <- jags.parallel(d, inits, param, model.file="rats.bug", n.chains=3, n.iter=2000) Error: could not find function

May I request that Dirk's package for jags be added to the CRAN archives for Debian and Ubuntu? Installing the rjags package for R requires specific versions of jags to be present on the system. The current version of rjags requires jags version 2.2.0 or later but the version on the Ubuntu archives at Canonical (i.e. not the CRAN archives) is 2.1.0-2 I can always install Dirk's package

Hello, I can`t figure out how to include a text file for use in an example in the .Rd help files of an R package I am writing. I want the examples section of one help file to look like this: \examples{ # Load the JAGS model mod <- jags.model("model.txt") } The function jags.model tries to read in the file model.txt. So far every time I run R CMD check, I get an error message:

Has anybody had issues running MCMC (either BUGS or JAGS) on data sets of this magnitude (ie 30k x 20-30). I've been trying to run a hierarchical random effects model on expression data but R completely stalls out on jobs run on 32bit R on our server (doesn't respond...then eventually crashes out with an exception fault). Would using 64bit R help with JAGS? (As far as I know there's

There is a thread on this topic already: http://finzi.psych.upenn.edu/Rhelp10/2010-August/250934.html I'm rather mystified by a similar problem and wondering whether I've overlooked something obvious. I'm running with latest versions of R and all packages, and latest version of JAGS running under Windows 7. Here's the problem. I have some source code. It's given below -

Hello, In WinBUGS 1.4 manual (http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/manual14.pdf), the gamma density is presented as dgamma(r,mu) where r and mu are the shape and rate parameters, respectively. In JAGS (rjags) manual version 1.0.2, May 9, 2008 (http://www-fis.iarc.fr/~martyn/software/jags/jags_user_manual.pdf), on page 26 the gamma density is presented as dgamma(mu,r) instead of dgamma(r,mu).

Could anyone give me some clues as to the best way to debug this error message? I think it is from the passing of variables back to R from the jags function which does Bayesian fitting. The curious part for me is that the error messages seem random, yet the input data are always the same. Any suggestions most welcome. Thanks J Compiling model graph Resolving undeclared variables

Frank (or anyone else), can you offer any comments comparing runjags, R2jags, rjags ? I couldn't find any vignettes, nothing except a brief mention on Task Views. Kevin On Wed, Oct 7, 2009 at 7:48 AM, Frank E Harrell Jr <f.harrell@vanderbilt.edu > wrote: > Have you tried the rjags package which uses the jags system? It is much > more integrated into R and works quite well.

Hi, I'm trying to verify the calculation of coefficient of determination (r squared) for linear regression. I've done the calculation manually with a simple test case and using the definition of r squared outlined in summary(lm) help. There seems to be a discrepancy between the what R produced and the manual calculation. Does anyone know why this is so? What does the multiple r squared

Hola, buenas a todos: Me dispongo a empezar un proyecto con logística bayesiana y sé que hay varios paquetes que puedo utilizar, arm, Bayelogit y MCMCpack. Me preguntaba si alguien tiene experiencia con éstos paquetes y me pueda decir cuál de ellos es mejor. Además de esto quería saber si sabíais alguna bibliografía para informarme mejor sobre lógica bayesiana, tengo algunas referencias,

Dear R users, I am trying to carry out MLE of the time-varying CAPM using the FKF package. My approach so far has been to try and adapt the example given in the help file found using ?fkf which demonstrates the MLE of an ARMA(2,1) model. When I attempt to run my R code (given below) I get the following error: Error in fkf(a0 = sp$a0, P0 = sp$P0, dt = sp$dt, ct = sp$ct, Tt = sp$Tt, : Some of

Greetings, I am using rpart for classification with "class" method. The test data is the Indian diabetes data from package mlbench. I fitted a classification tree firstly using the original data, and then exchanged the order of Body mass and Plasma glucose which are the strongest/important variables in the growing phase. The second tree is a little different from the first one. The

Hello, The likelihood includes two parameters to be estimated: lambda (=beta0+beta1*x) and alpha. The algorithm for the estimation is as following: 1) with alpha=0, estimate lambda (estimate beta0 and beta1 via GLM) 2) with lambda, estimate alpha via ML estimation 3) with updataed alpha, replicate 1) and 2) until alpha is converged to a value I coded 1) and 2) (it works), but faced some

Hi, I'm trying to get maximum likelihood estimates of \alpha, \beta_0 and \beta_1, this can be achieved by solving the following three equations: n / \alpha + \sum\limits_{i=1}^{n} ln(\psihat(i)) - \sum\limits_{i=1}^{n} ( ln(x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} 1/(psihat(i)) - (\alpha+1) \sum\limits_{i=1}^{n} ( 1 / (x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} (

Ubuntu R users, Early this month, version 3.0 of JAGS was released on its Sourceforge page. Dirk Eddelbuettel and I quickly rolled up packages for Debian and Ubuntu, respectively. If you are an Ubuntu user who utilizes my Launchpad PPA for your R related .deb files, JAGS was updated automatically. The downside to this is that JAGS 3.0 is not compatible with the R package rjags, also found

Dear All I'm attempting to speed up my model building procedure, but need some help with the loops I've created...please bear with me through the explanation! My basic model call is something like: m0sulf.nlme<-nlme(conc~beta0*exp(-beta1*day)+beta2*exp(-beta3*day), data=m0sulf, fixed=(beta0+beta1+beta2+beta3~1),