ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
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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.
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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.
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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.
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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 \(B\).
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interface  pm_sampleCov::setCovMerged
 Return the merged covariance of a sample resulting from the merger of two separate (potentially weighted) samples \(A\) and \(B\).
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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 \(B\).
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interface  pm_sampleCov::setCovUpdated
 Return the covAariance resulting from the merger of two separate (potentially weighted) non-singular and singular samples \(A\) and \(B\).
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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.
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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"