Hi Jane: On Mon, Aug 23, 2010 at 8:05 PM, rusers.sh <rusers...@gmail.com> wrote:
> 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. > Using an example adapted from package mvtnorm: library(mvtnorm) sigma <- matrix(c(1, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 1), ncol = 3) sigma [,1] [,2] [,3] [1,] 1.0 0.5 0.5 [2,] 0.5 1.0 0.5 [3,] 0.5 0.5 1.0 x <- rmvnorm(n = 1000, mean = c(1, 5, 10), sigma = sigma) head(x, 2) [,1] [,2] [,3] [1,] 1.1830181 6.730525 10.687912 [2,] 2.2911587 5.978146 9.493432 cov(x) [,1] [,2] [,3] [1,] 0.9725893 0.4894247 0.4902096 [2,] 0.4894247 0.9782143 0.4572949 [3,] 0.4902096 0.4572949 0.9656340 colMeans(x) [1] 0.9901327 5.0008999 10.0162695 # Same example using mvrnorm() from MASS: library(MASS) x2 <- mvrnorm(n = 1000, mu = c(1, 5, 10), Sigma = sigma) head(x2, 2) [,1] [,2] [,3] [1,] -0.1559149 3.449327 7.967966 [2,] -0.7961951 4.636752 8.580032 cov(x2) [,1] [,2] [,3] [1,] 1.0786150 0.4719868 0.5082440 [2,] 0.4719868 0.9608204 0.4819515 [3,] 0.5082440 0.4819515 1.0264072 colMeans(x2) [1] 1.042077 5.011792 10.025397 Package mvtnorm also has a function to obtain samples from multivariate-t distributions (rmvt). See the help pages of these functions for examples and further details. For simulating random fields, there are two packages of which I'm aware: RandomFields and FieldSim. It might also be worth checking out the Spatial Task View @ CRAN to see if anything else is available to help you. HTH, Dennis 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.
