ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
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pm_distMultiNorm Module Reference

This module contains classes and procedures for computing various statistical quantities related to the MultiVariate Normal (MVN) distribution. More...

Data Types

type  distMultiNorm_type
 This is the derived type for signifying distributions that are of type MultiVariate Normal (MVN) as defined in the description of pm_distMultiNorm. More...
 
interface  getMultiNormLogPDF
 Generate and return the natural logarithm of the Probability Density Function (PDF) of the MultiVariate Normal distribution as defined in the description of pm_distMultiNorm. More...
 
interface  getMultiNormLogPDFNF
 Generate and return the natural logarithm of the normalization coefficient of the Probability Density Function (PDF) of the MultiVariate Normal distribution as defined in the description of pm_distMultiNorm. More...
 
interface  getMultiNormRand
 Generate and return a (collection) of random vector(s) of size ndim from the ndim-dimensional MultiVariate Normal (MVN) distribution, optionally with the specified input mean(1:ndim) and the specified subset of the Cholesky Factorization of the Covariance matrix of the MVN distribution. More...
 
interface  setMultiNormRand
 Return a (collection) of random vector(s) of size ndim from the ndim-dimensional MultiVariate Normal (MVN) distribution, optionally with the specified input mean(1:ndim) and the specified subset of the Cholesky Factorization of the Covariance matrix of the MVN distribution. More...
 

Variables

character(*, SK), parameter MODULE_NAME = "@pm_distMultiNorm"
 

Detailed Description

This module contains classes and procedures for computing various statistical quantities related to the MultiVariate Normal (MVN) distribution.

Specifically, this module contains routines for computing the following quantities of the MultiVariate Normal distribution:

  1. the Probability Density Function (PDF)
  2. the Cumulative Distribution Function (CDF)
  3. the Random Number Generation from the distribution (RNG)
  4. the Inverse Cumulative Distribution Function (ICDF) or the Quantile Function

The PDF of the MVN distribution with the mean vector \(\bu{\mu}\) and covariance matrix \(\bu{\Sigma}\) at a given input point \(X\) is defined as,

\begin{equation} \large \pi\big(\bu{X} ~|~\bu{\mu}, \bu{\Sigma}\big) = \frac{1}{\sqrt{\big| 2\pi\bu{\Sigma} \big|}} ~ \exp\bigg( -\frac{1}{2}(\bu{X}-\bu{\mu})^T ~ \bu{\Sigma}^{-1} ~ (\bu{X}-\bu{\mu}) \bigg) ~, \end{equation}

which is defined if and only if the \(\bu{\Sigma}\) is positive-definite. The term \(\large \frac{1}{\sqrt{\big| 2\pi\bu{\Sigma} \big|}}\) is the Normalization Factor or the Normalization Constant of the MVN PDF whose natural logarithm can be computed via getMultiNormLogPDFNF in this module.

See also
pm_distUnif
pm_distNorm
pm_distMultiNorm
pm_distUnifEll
pm_distUnifPar
Applied Multivariate Statistical Analysis, Johnson, Wichern, 1998, 4th ed.
Test:
test_pm_distMultiNorm


Final Remarks


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For details on the naming abbreviations, see this page.
For details on the naming conventions, see this page.
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Author:
Amir Shahmoradi, Oct 20, 2009, 9:12 PM, Michigan

Variable Documentation

◆ MODULE_NAME

character(*, SK), parameter pm_distMultiNorm::MODULE_NAME = "@pm_distMultiNorm"

Definition at line 70 of file pm_distMultiNorm.F90.