Module Library |
generates a random sample from a multivariate normal distribution
The following example generates 1000 samples from a two-dimensional
multivariate normal
distribution with mean vector ,
correlation matrix Corr, and variance vector Var.
Each row of the returned matrix x is a row vector
sampled from the multivariate normal distribution.
The example then computes the sample mean and covariance and compares
them with the expected values. Here are the code and the output:
call randseed(1); N=1000; Mean = {1 2}; Corr = {0.6 0.5,0.5 0.9}; Var = {4 9}; /*create the covariance matrix*/ Cov = Corr # sqrt(Var` * Var); x = RANDNORMAL( N, Mean, Cov ); SampleMean = x[:,]; n = nrow(x); y = x - repeat( SampleMean, n ); SampleCov = y`*y / (n-1); print SampleMean Mean, SampleCov Cov; SampleMean Mean 1.0619604 2.1156084 1 2 SampleCov Cov 2.5513518 3.2729559 2.4 3 3.2729559 8.7099585 3 8.1
For further details about sampling from the multivariate normal distribution, see Gentle (2003, p. 197).
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