similar to: using R functions in a C loop

Hi. Here is a piece of cpp code. It works, but I do not understand the rational for the use of "R::dpois" to call the function dpois since in the examples I have always found directly "dpois" or "Rcpp::dpois" that both do not work in my code. Could anyone be so patient to explain me why should it be like that? Thaks a lot, Enrico #include <Rcpp.h> using

Hello everyone! First of all, please note that I'm working under Windows 7. I have written a Gibbs sampler in R and I'm now in the process of translating it in C++ to increase the speed. I'm relatively new to C++ and this question may be trivial, but my search so far have been unsuccessful. In my Gibbs sampler I am using some basic R functions (like the rep function for example)

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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

Dear r developers, I'm writing a set of new functions for an existing R package on R-forge (called COGARCH). I wrote the new R code (but still no documentation), and updated the NAMESPACE file. I installed it from my local repository and everything seems to work. I checked the local repository and the check did not produces errors, but 2 warnings and 2 notes (I attach the log) one of which

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 have to draw samples from an asymmetric-Laplace-Normal distribution: f(u|y, x, beta, phi, sigma, tau) \propto exp( - sum( ( abs(lo) + (2*tau-1)*lo )/(2*sigma) ) - 0.5/phi*u^2), where lo = (y - x*beta) and y=(y_1, ..., y_n), x=(x_1, ..., x_n) -- sorry for this huge formula -- A WinBUGS Gibbs sampler and the HI package arms sampler were used with the same initial data for all parameters. I

Dear R-users I have a problem choosing initial points for the function arms() in the package HI I intend to implement a Gibbs sampler and one of my conditional distributions is nonstandard and not logconcave. Therefore I'd like to use arms. But there seem to be a strong influence of the initial point y.start. To show the effect I constructed a demonstration example. It is reproducible

Hello ALL! Some times ago I started to learn and play with Bayesian stuffs. Many advice use of WinBUGS for Bayesian inference Using Gibbs Sampler. However, WinBUGS is discontinued, and now, development is under OpenBUGS. I wasn't lazy, so I installed both and tried out. In more than 90% of cases they give comparable outcome. But in few cases I got substantial differences. Recently, I read nice

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]]

Hello all. I'm developing a package for R holding a Gibbs sampler, which tends to have better performance when written in C than in R. During each iteration in the Gibbs sampler, I need the inverse of a symmetric matrix. For this, I wish to use lapack, as is concisely suggested in "Writing R extensions", since this will have better performance than I could ever write myself. After

Dear R users, I'm trying to carry out monte carlo integration of a posterior density function which is the product of a normal and a gamma distribution. The problem I have is that the density function always returns 0. How can I solve this problem? Here is my code #generate data x1 <- runif(100, min = -10, max = 10) y <- 2 * x1^2 + rnorm(100) # # # # # # # # Model 0 # # # # # # #

Hello all... I am just starting to teach myself Bayesian methods, and am interested in learning how to use UMacs. I've read the documentation, but the single example is a bit over my head at the level I am at right now. I was wondering if anyone has any simple examples they'd like to share. I've successfully done a couple of simple gibbs examples, but have had a hard time

Hi all, I am trying to run rejection sampling for the quantity z11 in the function below. Unfortunately I can't simplify the function further so that z11 only appears once. Whenever I run the algorithm, R looks as if it is running it (no error messages or anything), but then nothing happens for minutes...how long should it take to run something like this in R? I have tried in in both linux

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Dear Partecipants to the list, I am Enrico Foscolo, a student of the Faculty of Statistics, University of Bologna, and I am interested under consideration of the search of zeros of one function. I would want to write a code using the software R. I have already read the book "Computing the Zeros of Analytic Functions" (P. Kravanja and M. Van Barel, 2000) that speaks about this problem,

Check the rights before the folder your trying to change. Im guessing that now has 770, try 771 or 775 or 777 Greetz, Louis > -----Oorspronkelijk bericht----- > Van: Enrico Morelli [mailto:morelli at cerm.unifi.it] > Verzonden: dinsdag 30 juni 2020 14:44 > Aan: samba at lists.samba.org > CC: L.P.H. van Belle > Onderwerp: Re: [Samba] Users, home directories and profiles

We were promised this package last spring but I can't find it anywhere! Does anyone have any info? Thanks. >From RNews: "Umacs (Universal Markov chain sampler) is an R package (to be released in Spring 2006) that facilitates the construction of the Gibbs sampler and Metropolis algorithm for Bayesian inference ..." -- View this message in context:

On Wed, 8 Jul 2020 11:36:50 +0100 Rowland penny via samba <samba at lists.samba.org> wrote: > On 08/07/2020 09:57, Enrico Morelli wrote: > > On Wed, 8 Jul 2020 09:13:37 +0100 > > Rowland penny via samba <samba at lists.samba.org> wrote: > > > >> On 08/07/2020 08:06, Enrico Morelli wrote: > >>> On Wed, 1 Jul 2020 13:03:50 +0100 >