Multivariate Distribution Functions

Class providing multivariate distribution functions.

Default implementation: distributionFunctionMultivariateNormal

Methods

density → double precision

Return the probability density at x.

  • double precision, intent(in ), dimension(:) :: x

  • logical , intent(in ), optional :: logarithmic

  • integer , intent( out), optional :: status

cumulative → double precision

Return the cumulative probability between xLow, and xHigh. The cumulative distribution is defined as \(P(x_1 < X_1,\ldots,x_N < X_N)\) where \(\mathbf{X}=\)x.

  • double precision, intent(in ), dimension(:) :: xLow , xHigh

  • logical , intent(in ), optional :: logarithmic

  • integer , intent( out), optional :: status

distributionFunctionMultivariateNormal

A multivariate normal distribution.

(Default implementation)

Methods

  • cumulativeMonteCarlo — Compute the cumulative distribution function used Monte Carlo methods.

Parameters

  • [mean] — The mean of the multivariate normal distribution.

  • [covariance] — The covariance of the multivariate normal distribution.

  • [errorAbsolute] — The absolute error tolerance in determining the cumulative distribution function.

  • [errorRelative] — The relative error tolerance in determining the cumulative distribution function.

  • [countTrialsMaximum] — The maximum number of trials allowed in Monte Carlo evaluation of the cumulative distribution function.