mvnpdf - Multivariate normal probability density function
Syntax
y = mvnpdf(X)
y = mvnpdf(X,MU)
y = mvnpdf(X,MU,SIGMA)
Description
y = mvnpdf(X) returns the n-by-1 vector y,
containing the probability density of the multivariate normal distribution
with zero mean and identity covariance matrix, evaluated at each row
of the n-by-d matrix X.
Rows of X correspond to observations and columns
correspond to variables or coordinates.
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.
If MU is a matrix, 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 a 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 vector
or a 1-by-d-by-n array, containing
just the diagonal. Specify [] for MU to
use its default value when you want to specify only 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.
Examples
mu = [1 -1];
SIGMA = [.9 .4; .4 .3];
X = mvnrnd(mu,SIGMA,10);
p = mvnpdf(X,mu,SIGMA);
See Also
mvncdf, mvnrnd
Multivariate Normal Distribution
 | mvncdf | | mvregress |  |
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