similar to: Simulating from a Normal Inverted Wishart distribution

Hello Everyone Both the MCMCpack and the bayesm libraries allow us to make draws from the Inverse Wishart distribution. But I wanted to find out how exactly is the Inverse Wishart distribution parameterized in these libraries. The reason I ask is the following: Now its generally standard to express Inverse Wishart as IW(0.5 * DOF,0.5* Scale). (DOF-> Degree of freedom, Scale -> Scale

Hello everyone Is there a function/command to simulate from "matrix variate normal distribution" in R. A follow up question would be is there a function/command to obtain the density, distribution and quantile function of "matrix variate normal distribution" in R. Wikipedia has a good description of "matrix variate normal distribution" which is also alternatively

Dear R users, I am doing MCMC using Metropolis-Hastings. My model is bivariate-log-normal and the prior for variance-covariance is wishart distribution. I am wondering if there are some simple codes about how to get the density of Wishart distribution in my case ? Thanks in advance. Meihua [[alternative HTML version deleted]]

Hi, I am not sure if this make sense at all. I'd like to sample a matrix, which follows a wishart / inverted wishart distribution. However, the (1,1) element of this matrix should always be equal to 1. How can I handle it in R? Any suggestion is greatly appreciated. Thanks a lot. Sonia [[alternative HTML version deleted]]

Hello Everyone I have a dual-core Intel i3-370M processor and Windows 64 operating system. I have a 3GB RAM and my processor can support a maximum of 8GB RAM. I have virtual memory enabled on my computer. I am running a program in the 64 bit R which implements a MCMC on a large dataset and involves around 80000 iterations. The processor estimates that it will take around 1000 minutes to

Hello Everyone I have a MCMC loop to calculate a time varying hierarchical Bayesian structure. This requires me to use around 5-6 matrix inversions in the loop. I use cholesky and chol2inv for the matrix decomposition. Because of the data I am working with I am required to invert a 167 by 167 matrix twice in one iteration. I need to run the iteration for 10000 times, but I get the error

If so, I''ve had trouble finding it. Can anyone help?

R users- In moving from R 2.0.0 to R 2.1.0 in Windows, I have encountered a problem with the "riwish" command in the package "MCMCpack". I've searched the documentation and can't seem to figure it out. For example: Define a matrix: > lam <- matrix(c(.00233,-.00057,-.00057,.00190),2,2) and then use the riwish command to generate a random inverse-Wishart

Dear R users, I would like to make my R code for MCMC faster. It is possible to integrate C code into R but I think C is too complicated for me. I would need a C introduction only for MCMC and I do not know if such a thing exists. I was thinking of Python (and scipy). Where could I read about its integration into R ? How developed are the statistical packages in Python ? I could not find a

Hi Thanks for replying my question! What really interested me is that the package providing some complex form sampling, such as wishart, multinomial, dirichlet. And others for example conditional beta distribution confining the random variable in the interval (a, b). Since these concept are widely used in the baysian, I wonder whether somebody has already written this package. Thanks! Best

I want to generate a valid variance-covariance matrix. One way could be to generate some random sample from multivariate normal distribution and then calculate cov. matrix. Another way could be to sample from wishart distribution itself. However both cases need a valid i.e. PD covariance matrix. As I need to generate that covariance matrix only, I am not interested those two methods. Can anyone

Dear useRs, I have written a function that implements a Bayesian method to compare a patient's score on two tasks with that of a small control group, as described in Crawford, J. and Garthwaite, P. (2007). Comparison of a single case to a control or normative sample in neuropsychology: Development of a bayesian approach. Cognitive Neuropsychology, 24(4):343?372. The function (see

Respected R Users, I looking for help with generating theoretical confidence regions for any of non-symmetric bivariate statistical distributions (bivariate Chi-squared distribution<Wishart distribution>, bivariate F-distribution, or any of the others). I want to to used it as a benchmark to compare a few strategies constructing confidence regions for non-symmetric bivariate data. There is

Dear List, Is there any function in R to generate multivariate F distribution with given correlation/covariance matrix? Actually, I just want to generate some 2-dimentional non-normal data sets (skewed) for low (may be around 0.3 cor coeff.) negatively and also positively correlated variables ? Thanks in advance. Anna

hello sir im working on text classification using java and r programming i start with exporting a document term matrix (tdm) from my java programme using corpus and now i try to apply knn algorithem using the matrix and r but i cant do that any help sir here my data here my script https://mega.nz/#!Q6J2ibAA!4PadiOKbP7rLodyiRrVsdKl-D2ZP7LYm0gaz94uBmF8 itry to post put icant whay!!

Dear All, Is there any function in R for computing "multivariate chi-square distribution"? How about "multivariate gamma distribution"? I appreciate any comment on this subject. Thank you, Amin Zollanvari PhD student Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX

Hola! Para simular matrices de datos normales multivariados con la sentencia rmvnorm (dentro del paquete mvtnorm) se necesita, entre otras cosas, el número de vectores a simular, el vector de parámetros-medias correspondiente a cada variable y su respectiva matriz de Varianza-Covarianza. En este último punto, tengo problemas. En lugar de ingresar una matriz sigma creada por mi, necesito simular

Hello, I am a chemical student and I make use of 'lme/lmer function' to handle experiments in split-plot structures. I know about the mcmcsamp and I think that it's very promissory. I would like knowing "the concept behind" of the mcmcsamp function. I do not want the C code of the MCMCSAMP function. I would like to get the "pseudo-algorithm" to understanding that

Hello R group Do you know if an EM algorithm exits for R to estimate missing data in a sample? I just found knn algorithm in to the package emv but it doesn't look to be the usual EM algorithm. Thanks Xavier -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Hi, Does anybody know, what is going on here? > diag(sqrt(1)) [,1] [1,] 1 > diag(sqrt(0.3333)) <0 x 0 matrix> > sqrt(1) [1] 1 > sqrt(0.3333) [1] 0.5773214 BR, Markku Karhunen researcher University of Helsinki