represents a multivariate normal (Gaussian) distribution with mean vector μ and covariance matrix Σ.
- The probability density for vector in a multivariate normal distribution is proportional to .
- The mean μ can be any vector of real numbers, and Σ can be any symmetric positive definite × matrix of real numbers with p=Length[μ].
- MultinormalDistribution can be used with such functions as Mean, CDF, and RandomVariate.
Introduced in 2010