Density and log-density for the multivariate normal distribution
with mean equal to mu
and variance matrix equal to sigma.
dmvnorm(y, mu=NULL, sigma=NULL)
logdmvnorm(y, mu=NULL, sigma=NULL)dmvnorm gives the densities, while
logdmvnorm gives the logarithm of the densities.
Either a \(d\) - vector or an \(n\times d\) matrix, where \(d\) is the dimension of the normal distribution and \(n\) is the number of points at which the density is to be evaluated.
\(d\) - vector: Mean of the normal distribution (or NULL uses the origin as default)
This \(d\times d\) matrix is the variance matrix of the normal distribution (or NULL uses the identity matrix as default)
This code is written to be efficient, using the qr-decomposition of the
covariance matrix (and using it only once, rather than recalculating it
for both the determinant and the inverse of sigma).