Hi, If you see the link http://www.stata.com/help.cgi?drawnorm, and you can see an example, #draw a sample of 1000 observations from a bivariate standard normal distribution, with correlation 0.5. #drawnorm x y, n(1000) corr(0.5) This is what Stata software did. What i hope to do in R should be similar as that. It will be better to only need us to specify the correlation matrix, mean values and possible variances. One of my aim is to simulate random fields. Thanks.
2010/8/23 Ben Bolker <bbol...@gmail.com> > rusers.sh <rusers.sh <at> gmail.com> writes: > > > rmvnorm()can be used to generate the random numbers from a multivariate > > normal distribution with specified means and covariance matrix, but i > want > > to specify the correlation matrix instead of covariance matrix for the > > multivariate > > normal distribution. > > Does anybody know how to generate the random numbers from a multivariate > > normal distribution with specified correlation matrix? What about > > other non-normal > > distribution? > > What do you want the variances to be? If you don't mind that they're > all equal to 1, then using your correlation matrix as the Sigma argument > to the mvrnorm() [sic] function in MASS should work fine. They have to > be defined as *something* .... > If you want multivariate distributions with non-normal marginal > distributions, consider the 'copula' package, but be prepared to do > some reading -- this is a fairly big/deep topic. > > good luck. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- ----------------- Jane Chang Queen's [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
