MultiNormal
MultiNormal( m, s, c, i, j )
A multi-variate normal (or Gaussian) distribution with mean m, standard deviation s, and correlation matrix cm. m and s may be scalar or indexed by i. cm must be symmetric, positive-definite, and indexed by i & j, which must be the same length.
Multinormal uses a correlation matrix. Compare with Gaussian, which also defines a multi-variate normal but which uses a covariance matrix.
Library
Multivariate Distribution.ana
Notes
MultiNormal can be used with the Random function to generate a single multivariate sample point, indexed by I. E.g.:
Random( MultiNormal(m,s,c,i,j) )
To generate independent samples along one or more indexes K1,K2,K3, use the Over parameter, e.g.:
MultiNormal(m,s,c,i,j,Over:K1,K2,K3)
See Gaussian for an example.
See Also
- Gaussian : Multivariate normal specified using covariance rather than correlation.
- Normal : 1-D normal distribution
- BiNormal, Normal_correl : 2-D normal distributions
- Random
Comments
Enable comment auto-refresher