similar to: Multivariate Normal and loops

Hi everyone, i'm not very good with R, and i know that my question is quite simple. I generated this vector for a sample of 100 and i want to know how to save these as ez1, ez1, ez3...ez100. I guess i have to do it by "for", but i didn't succeed.. i put here my output ezt [1] -0.05470228 -1.76356668 -1.68843463 -0.77283767 0.25077826 -0.65236833 1.05230056 -0.48900254

Hello, I would like to simulate randomly from a multivariate normal distribution using a correlation matrix, rho. I do not have sigma. I have searched the help archive and the R documentation as well as doing a standard google search. What I have seen is that one can either use rmvnorm in the package: mvtnorm or mvrnorm in the package: MASS. I believe I read somewhere that the latter was

I must to create an array with dimensions 120x8x500. Better I have to make 500 simulations of 8 series of return from a multivariate normal distribution. there's the command "mvrnorm" but how I can do this repeating the simulation 500 times?" [[alternative HTML version deleted]]

For example, the correlation matrix is 3x3 and looks like 1 0.75 0 0 0 0.75 1 0 0 0 0 0 0 0 0 Can I write the code like this? p<- 3 # number of variables per observation N<- 10 # number of samples # define population correlation matrix sigma sigma<-matrix(0,p,p) #creates a px p matrix of 0 rank<-2 for (i in 1:rank){ for (j in 1:rank){ rho<-0.75

Please, I would like to know how to generate a truncated multivariate normal distribution k - dimensional, X ~ NT(mu, Sigma), where the elements of X to be non-negative (except the first), and the first dimension is strictly larger than zero. Example: X ~ NT_2(mu, Sigma), where mu=c(0.5, 0.5) and Sigma=c([120, 191], [191,154]), with X_1>0 and X_2>=0 Could anybody help

Dear everyone, I am having problem simulating multivariate data. Though I was able to simulate the data, but finding the variance-covariance matrix of simulated data did not give exact covariance matrix used in simulating the data. Unlike some other packages, like stata, using command "corr2data" will simulate data having the covariance matrix exactly with the specified covariance

Dear all, In MATLAB, to generate multivariate F with specified correlation matrix Pn I can use the code such as Z = mvnrnd([0 0 0 0 0], Pn, N); U = normcdf(Z,0,1); X = [finv(U(:,1),5,15) finv(U(:,2),5,15) finv(U(:,3),5,15) finv(U(:,4),5,15) finv(U(:,5),5,15)]; Is there something similar in R? Thank you for your time.

Hey, I am confused about how to generate the sample data from a mixture of Multivariate Gaussian ditribution. For example, there are 2 component Gaussian with prior probability of 0.4 and 0.6, the means and variances are u1=[1 1]', Cov1=[1 0;0 1] and u2=[-1 -1]', Cov2=[1 0;0 1] repectively. So how can I generate a sample of 500 data from the above mixture distribution? Thanks. Fred

Hello, I have a question about multivariate Shapiro-Wilks test. I tried to analyze if the data I have are multivariate normal, or how far they are from being multivariate normal. However, any time I did >mshapiro.test(mydata) I get the message: Error in solve.default(R %*% t(R), tol = 1e-18) : system is computationally singular: reciprocal condition number = 5.38814e-021 I tried

To whom it may concern, I try to simulate a non-normal multivariate distribution. The MASS package allows by mean of "mvrnorm" command to perform a multivariate normal simulation. Is there an equivalent command for an arbitrary multivariate distribution available in the R-language? Thank you in advance. Bernard Colin Colin Bernard Professeur titulaire D?partement de Math?matiques et

I would like to estimate a 95% highest density area for a multivariate parameter space (In the context of anova). Unfortunately I have only experience with univariate kernel density estimation, which is remarkebly easier :) Using Gibbs, i have sampled from a posterior distirbution of an Anova model with k means (mu) and 1 common residual variance (s2). The means are independent of eachother, but

Dear all, I created a n*2 matrix and I want to replace the ith row with a vector. Can anyone suggest me what is the simple way to do it? Sorry for bothering you with such simple question. I appreciate any hints or advice. Thanks in advance. Cassie [[alternative HTML version deleted]]

Dear?All, ? a few weeks ago I have posted a question on the R help listserv that?some of you have responded to with a great solution, would like to thank you for that? again.?I thought I would reach out to you with the issue I am trying to solve now. I have posted the question a few days ago, but probably it was not?clear enough, so I thought i try it again.?At times I have a multivariate example

Dear all, I am trying to simulate from truncated Pareto distribution. I know there is a package called PtProcess for Pareto distribution...but it is not for truncated one. Can anyone please help me with this? Thanks in advance. Cassie [[alternative HTML version deleted]]

Hello. Somebody knows how can I generate a set of n random vectors of a normal distribution of several variables? For example, I want to generate n=100 random vectors of two dimensions for a normal with mean c(0,1) and variance matrix: matrix(c(2,1,1,3),2,2). Thanks in advance, Arnau.

Dear all, I am trying to simulate from discrete uniform distribution. But I could not find any in-built code in R. Could anyone help me please? Thanks in advance for the time and help. Cassie [[alternative HTML version deleted]]

Dear all, I have a data set which has latitude, longitude (not in increasing order) and observed precipitation corresponding to those locations. I am using image.plot command for that. But I want to overlay a map of US on that plot. I know we can use map('usa') to draw it, but I dont know how can I overlay it on the plot of the precipitation data. Can anyone please help me with it?

Dear all, I am trying to define an array as follows: a=array(NA,c(m,2,N,G)), Even though the numbers N and G are fixed, m is a vector. So, I can't define 'a' as above. For eg, N=3 G=6, but m=c(2,7,5) and length(m)=N. Can anyone suggest me how can I define 'a' when m is a vector? Thanks in advance for your help. Cassie [[alternative HTML version deleted]]

Does anyone know how to do a fry plot in R? I have 600-800 points per image, and I really don't want to attempt that manually. Thank you! Cassie [[alternative HTML version deleted]]

I am having a hard time putting the below into a loop, where it pulls out ppt from all he stations I have versus having to go through and hard code the data to the specific stations. I tried stnID <- stnid[which(duplicated(stnid)==FALSE)] for(i in 1:length(stnID)) { ppt[i] <- ppt[which(stnid==[i])] } but it doesn't like to use the which function inside a for loop? Any idea's here is