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

pm_sampleCov.F90 File Reference

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## Data Types | |

interface | pm_sampleCov::getCov |

Generate and return the (optionally unbiased) covariance matrix of a pair of (potentially weighted) time series `x(1:nsam)` and `y(1:nsam)` or of an input (potentially weighted) array of shape `(ndim, nsam)` or `(nsam, ndim)` where `ndim` is the number of data dimensions (the number of data attributes) and `nsam` is the number of data points.More... | |

interface | pm_sampleCov::setCov |

Return the covariance matrix corresponding to the input (potentially weighted) correlation matrix or return the biased sample covariance matrix of the input array of shape `(ndim, nsam)` or `(nsam, ndim)` or a pair of (potentially weighted) time series `x(1:nsam)` and `y(1:nsam)` where `ndim` is the number of data dimensions (the number of data attributes) and `nsam` is the number of data points.More... | |

interface | pm_sampleCov::setCovMean |

Return the covariance matrix and mean vector corresponding to the input (potentially weighted) input `sample` of shape `(ndim, nsam)` or `(nsam, ndim)` or a pair of (potentially weighted) time series `x(1:nsam)` and `y(1:nsam)` where `ndim` is the number of data dimensions (the number of data attributes) and `nsam` is the number of data points.More... | |

interface | pm_sampleCov::getCovMerged |

Generate and return the merged covariance of a sample resulting from the merger of two separate (potentially weighted) samples \(A\) and \(B\). More... | |

interface | pm_sampleCov::setCovMerged |

Return the merged covariance of a sample resulting from the merger of two separate (potentially weighted) samples \(A\) and \(B\). More... | |

interface | pm_sampleCov::setCovMeanMerged |

Return the merged covariance and mean of a sample resulting from the merger of two separate (potentially weighted) samples \(A\) and \(B\). More... | |

interface | pm_sampleCov::setCovUpdated |

Return the covAariance resulting from the merger of two separate (potentially weighted) non-singular and singular samples \(A\) and \(B\). More... | |

interface | pm_sampleCov::setCovMeanUpdated |

Return the covariance and mean of a sample that results from the merger of two separate (potentially weighted) non-singular \(A\) and singular \(B\) samples. More... | |

## Modules | |

module | pm_sampleCov |

This module contains classes and procedures for computing the properties related to the covariance matrices of a random sample. | |

## Variables | |

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