MVG Multivariate Gaussian random number generator

Generates vectors from the multivariate normal distribution parameterized by specified mean vector a
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Updated 4 Sep 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.

Cite As

Chad Lieberman (2024). MVG Multivariate Gaussian random number generator (https://www.mathworks.com/matlabcentral/fileexchange/21279-mvg-multivariate-gaussian-random-number-generator), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2007a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
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Version Published Release Notes
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