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The Multivariate Gaussian Distribution

The Multivariate Gaussian DistributionChuong B. DoOctober 10, 2008A vector-valued random variableX= X1 Xn Tis said to have amultivariatenormal (or Gaussian ) distributionwith mean Rnand covariance matrix Sn++1if its probability density function2is given byp(x; , ) =1(2 )n/2| |1/2exp 12(x )T 1(x ) .We write this asX N( , ). In these notes, we describe Multivariate Gaussians and someof their basic Relationship to univariate GaussiansRecall that the density function of aunivariate normal (or Gaussian ) distributionisgiven byp(x; , 2) =1 2 exp 12 2(x )2 .Here, the argument of the exponential function, 12 2(x )2, is a quadratic function of thevariablex.

diagonal covariance matrix Σ = diag(σ2 1,σ 2 2,...,σ 2 n) is the same as a collection of n indepen-dent Gaussian random variables with mean µi and variance σ2 i, respectively. 4 Isocontours Another way to understand a multivariate Gaussian conceptually is …

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