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MultinormalDistribution

MultinormalDistribution[Mu, CapitalSigma]
represents a multivariate normal (Gaussian) distribution with mean vector Mu and covariance matrix CapitalSigma.
  • The probability density for vector x in a multivariate normal distribution is proportional to ExponentialE-(x-Mu).CapitalSigma-1.(x-Mu)/2.
  • The mean Mu can be any vector of real numbers, and CapitalSigma can be any symmetric positive definite p×p matrix with p=Length[Mu].
  • MultinormalDistribution can be used with such functions as Mean, CDF, and RandomReal.
Needs["MultivariateStatistics`"]
The mean of a bivariate normal distribution with correlation Rho:
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Needs["MultivariateStatistics`"]
The variances of each dimension:
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Needs["MultivariateStatistics`"]
Probability density function:
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