Difference between revisions of "MultiUniform"

Line 1: Line 1:
[[category:Multivariate Distribution Functions]]
+
[[Category: Multivariate Distribution Functions]]
[[Category:Doc Status C]] <!-- For Lumina use, do not change -->
+
[[Category: Multivariate Distributions library functions]]
 +
[[Category: Doc Status C]] <!-- For Lumina use, do not change -->
 
   
 
   
 
== MultiUniform(corr, I, J, ''lb, ub'') ==
 
== MultiUniform(corr, I, J, ''lb, ub'') ==
Line 18: Line 19:
 
* [[Uniform]]
 
* [[Uniform]]
 
* [[Gaussian]]
 
* [[Gaussian]]
 +
* [[RankCorrel]]
 
* [[Multivariate distributions]]
 
* [[Multivariate distributions]]
 
* [[Distribution Densities Library]]
 
* [[Distribution Densities Library]]

Revision as of 18:42, 23 February 2016


MultiUniform(corr, I, J, lb, ub)

Full declaration:

MultiUniform(corr: Numeric[I, J]; I, J: IndexType; lb, ub: optional Numeric[I, J])

The multi-variate uniform distribution.

Generates vector samples (indexed by «I») such that each component has a uniform marginal distribution, and such that each component have the pair-wise correlations given by corr. Indexes «I» and «J» must have the same number of elements, corr needs to be symmetric and must obey a certain semidefinite condition (namely that the transformed matrix [2*sin(30*cov)] is positive semidefinite. In most cases, this roughly the same as corr being, or not being, positive semidefinite). «Lb» and «ub» can be used to specify upper and lower bounds, either for all components, or individually if these bounds are indexed by «I». If «lb» and «ub» are omitted, each component will have marginal Uniform(0, 1).

The correlation specified in corr is true sample correlation (Pearson correlation) - not rank correlation.

Library

Multivariate Distributions.ana

See Also

Comments


You are not allowed to post comments.