ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
See the latest version documentation. |

pm_distCov.F90 File Reference

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## Data Types | |

type | pm_distCov::gram_type |

This the derived type whose instances imply the use of the Gram algorithm for generating random covariance matrices. More... | |

type | pm_distCov::dvine_type |

This the derived type whose instances imply the use of the Dvine algorithm for generating random covariance matrices as described in algorithm of Lewandowski et al. (2009). More... | |

type | pm_distCov::onion_type |

This the derived type whose instances imply the use of the Onion algorithm for generating random covariance matrices as described in algorithm of Lewandowski et al. (2009). More... | |

interface | pm_distCov::getCovRand |

Generate and return a random positive-definite (correlation or covariance) matrix using the Gram method. More... | |

interface | pm_distCov::setCovRand |

Return a random positive-definite power-law-distributed (correlation) matrix. More... | |

## Modules | |

module | pm_distCov |

This module contains classes and procedures for generating random matrices distributed on the space of positive definite matrices, such that their determinants is uniformly or power-law distributed. | |

## Variables | |

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

type(gram_type), parameter | pm_distCov::gram = gram_type() |

The scalar constant of type gram_type implying the use of the Gram algorithm for generating random covariance matrices. More... | |

type(dvine_type), parameter | pm_distCov::dvine = dvine_type() |

The scalar constant of type dvine_type implying the use of the Dvine algorithm for generating random covariance matrices as described in algorithm of Lewandowski et al. (2009). More... | |

type(onion_type) | pm_distCov::onion = onion_type() |

The scalar module variable object of type onion_type implying the use of the Onion algorithm for generating random covariance matrices as described in algorithm of Lewandowski et al. (2009). More... | |