MVG Multivariate Gaussian random number generator

Version 1.0.0.0 (876 octets) par Chad Lieberman
Generates vectors from the multivariate normal distribution parameterized by specified mean vector a
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Mise à jour 4 sept. 2008

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MVG is a multivariate Gaussian (normal) random number generator. A user can generate a vector from the multivariate normal distribution of any dimension by specifying a mean vector and symmetric positive-definite covariance matrix. A linear transformation based on the Cholesky decomposition of the covariance matrix is applied to a set of realizations from the distribution N(0,I). By applying the linear transformation to those samples, the output is a matrix whose columns are samples drawn from the distribution N(mu,Sigma) where mu is the specified mean vector and Sigma is an SPD covariance matrix. Type help mvg to learn more.

Citation pour cette source

Chad Lieberman (2025). MVG Multivariate Gaussian random number generator (https://fr.mathworks.com/matlabcentral/fileexchange/21279-mvg-multivariate-gaussian-random-number-generator), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2007a
Compatible avec toutes les versions
Plateformes compatibles
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Version Publié le Notes de version
1.0.0.0

- used Cholesky decomposition to transform from N(0,I) to N(mu,Sigma)
- constructed appropriate H1 line
- used randn instead of generating approximate normals via rand and central limit theorem