similar to: Multivariate chi-square distribution function

Dear all, Is there any method in R to find all possible nonnegative integer solutions to the linear equation with unit coefficients as follow: X1+X2+...+Xk=N Thank you, Amin Zollanvari

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

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

Hi, I am looking for an efficient way to compute the values of the density function of a multivariate T distribution - something like "dmvnorm", but for T distr. Does this exist somewhere? Many thanks, Jan Bulla Goettingen University

Dear All, I think I have followed everything for building my first R package (Downloading Rtools, necessary files in necessary locations, no space in path and...). But when in command Prompt I write "Rcmd check mypackage" the first few steps are "OK" but then it gives the following error: checking whether package roots can be installed.....ERROR installation failed see

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 I was wondering how would one simulate from a Normal Wishart Distribution in R. A normal inverted Wishart distribution is denoted by NIW (M,C,d,S), where X/(Sigma) ~ N( M,C,(Sigma) ) -> a matrix normal distribution, (Sigma) -> column dispersion matrix (Sigma) ~ IW (d,S) -> inverted Wishart distribution Thanks a lot ! Best Shantanu [[alternative HTML version

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

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, This is not a HW problem, sadly: I was last in a classroom 30 years ago, and can no longer run off to the instructor :-( I apologize but I cut and paste the wrong snippet earlier and made a typo in doing so, but the result is the same with the more appropriate snippet. require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(data = xx,

library(mvtnorm) # you were misusing "require"... only use require if you plan to library(ggplot2) # test the return value and fail gracefully when the package is missing set.seed( 1234 ) xx <- data.frame( rmvt( 100, df = c( 13, 13 ) ) ) xx2 <- expand.grid( X1 = seq( -5, 5, 0.1 ) # all combinations... could be used to fill a matrix , X2 = seq( -5, 5, 0.1 )

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]]

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

Hello Ulrik, I apologize, but I can not see how to provide a pdf in place of the density function which calculates a KDE (that is, something from the dataset in the example). Can you please point to the specific example that might help? Here is what I get: require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(faithfuld, aes(waiting,

Hello, I want to draw a histogram of the mean of sample observations drawn from multivariate t distribution. I am getting the following error corresponding to the code I used. Though I am getting the graph, but I am curious to know the warning message. Warning messages: 1: In if (freq) x$counts else { : the condition has length > 1 and only the first element will be used 2: In if (!freq)

Hi, Are there some packages which can generate multi-normal, multi-t, etc multivariate sampling? thanks! Best wishes, Peng ******************************* Peng Zhang Department of Biostatistics Harvard School of Public Health 655 Huntington Avenue Boston, Massachusetts 02115 ******************************* I believe I can fly I believe I can touch the sky

Can someone please point me to an example with geom_contour() that uses a function? The help does not have an example of a function, and also I did not find anything from online searches. TIA, BFD ----------------------------------------------------------------------------------------------- How about geom_contour()? Am So., 8. Okt. 2017, 20:52 schrieb Ranjan Maitra <maitra at

> On Oct 9, 2017, at 6:03 AM, Big Floppy Dog <bigfloppydog at gmail.com> wrote: > > Hello Ulrik, > > I apologize, but I can not see how to provide a pdf in place of the density > function which calculates a KDE (that is, something from the dataset in the > example). Can you please point to the specific example that might help? > > Here is what I get: > >

I am desperately trying to impute missing data using 'imp.mix' but always run into this yucky error message to which I cannot find the solution. It's the first time I am using mix and I'm trying really hard to understand, but there's just this one step I don't get...perhaps someone knows the answer? Thanks! Jens My code runs: