Multivariate normal random variables
 GSL lacks a multivariate normal random variable option, so have implemented one using the eigenvalue decomposition (default method in the R function rmvnorm). Function should consider doing error handling (i.e. warning if covariance matrix isn't positive definite or if the vectors given don't match dimensions), though these may be mostly unnecessary cost. Also uses a general blas matrix multiplication when one of the matrices is just sqrt(eigenvalues) on the diagonal, so this could possibly be sped up considerably using the correct blas matrix multiply.
 As the solutions to the regimes model are still multivariate normal, simulating data sets just means drawing random numbers from this distribution, as opposed to actually evolving the SDE along the tree.
