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"