y = mvnpdf (x) returns the probability density of the multivariate normal distribution with zero mean and identity covariance matrix, evaluated at each row of x. Rows of the N-by-D matrix x correspond to observations orpoints, and columns correspond to variables or coordinates. y is an N-by-1 vector.

y = mvnpdf (x, mu) returns the density of the multivariate normal distribution with mean MU and identity covariance matrix, evaluated at each row of x. mu is a 1-by-D vector, or an N-by-D matrix, in which case the density is evaluated for each row of x with the corresponding row of mu. mu can also be a scalar value, which MVNPDF replicates to match the size of x.

y = mvnpdf (x, mu, sigma) returns the density of the multivariate normal distribution with mean mu and covariance sigma, evaluated at each row of x. sigma is a D-by-D matrix, or an D-by-D-by-N array, in which case the density is evaluated for each row of x with the corresponding page of sigma, i.e., mvnpdf computes y(i) using x(i,:) and sigma(:,:,i). If the covariance matrix is diagonal, containing variances along the diagonal and zero covariances off the diagonal, sigma may also be specified as a 1-by-D matrix or a 1-by-D-by-N array, containing just the diagonal. Pass in the empty matrix for mu to use its default value when you want to only specify sigma.

If x is a 1-by-D vector, mvnpdf replicates it to match the leading dimension of mu or the trailing dimension of sigma.

See also: mvncdf, mvnrnd

Source Code: mvnpdf