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Showing results 1 to 10 of 2,959.


Function dibas [adephylo v1.1-11]
keywords
multivariate
title
DIstance-Based Assignment
description
These functions are under development. Please do not use them unless asked by the author.
Function ppca [adephylo v1.1-11]
keywords
multivariate
title
Phylogenetic principal component analysis
description
These functions are designed to perform a phylogenetic principal component analysis (pPCA, Jombart et al. 2010) and to display the results.
Function cpt-package [cpt v1.0]
keywords
multivariate
title
Classification Permutation Test
description
Description: Non-parametric test for equality of multivariate distributions. Trains a classifier to classify (multivariate) observations as coming from one of several distributions. If the classifier is able to classify the observations better than would be expected by chance (using permutation inference), then the null hypothesis that the distributions are equal is rejected.
Function cpt [cpt v1.0]
keywords
multivariate
title
Classification Permutation Test
description
Non-parametric test for equality of multivariate distributions. Trains a classifier to classify (multivariate) observations as coming from one of several distributions. If the classifier is able to classify the observations better than would be expected by chance (using permutation inference), then the null hypothesis that the distributions are equal is rejected.
Function ASCOV_JADE [BSSasymp v1.2-1]
keywords
multivariate
title
Asymptotic covariance matrix of JADE and FOBI estimates
description
JADE solves the blind source separation problem in the case of independent components with at most one component having kurtosis values zero, while FOBI requires distinct kurtosis values. The functions compute the asymptotic covariance matrices of JADE and FOBI estimates for the mixing or the unmixing matrices.
Function ASCOV_JADE_est [BSSasymp v1.2-1]
keywords
multivariate
title
Asymptotic covariance matrix of JADE and FOBI estimates
description
JADE solves the blind source separation problem in the case of independent components with at most one component having kurtosis values zero, while FOBI requires distinct kurtosis values. The functions compute the asymptotic covariance matrices of JADE and FOBI estimates for the mixing or the unmixing matrix.
Function CRB [BSSasymp v1.2-1]
keywords
multivariate
title
Cramer-Rao bound for the unmixing matrix estimate in the independent component model.
description
Cramer-Rao bound for the unmixing matrix estimate in the independent component model.
Function ASCOV_FastICAdefl [BSSasymp v1.2-1]
keywords
multivariate
title
Asymptotic covariance matrices of different deflation-based FastICA estimates
description
The regular deflation-based FastICA finds the independent components one by one using a nonlinearity function. The adaptive deflation-based FastICA chooses, for each component separately, the best nonlinearity from a set of nonlinearities. This function computes asymptotic covariance matrices of the different deflation-based FastICA mixing and unmixing matrix estimates.
Function ASCOV_FastICAdefl_est [BSSasymp v1.2-1]
keywords
multivariate
title
Asymptotic covariance matrices of deflation-based FastICA estimates
description
The regular deflation-based FastICA finds the independent components one by one using a nonlinearity function. The adaptive deflation-based FastICA chooses, for each component separately, the best nonlinearity from a set of nonlinearities. This function computes estimates of the covariance matrices of the different deflation-based FastICA mixing and unmixing matrix estimates.
Function ASCOV_FastICAsym [BSSasymp v1.2-1]
keywords
multivariate
title
Asymptotic covariance matrix of symmetric FastICA estimates
description
Symmetric FastICA estimators solves the blind source separation problem in the case of independent components. These functions compute the asymptotic covariance matrices of the regular and the squared symmetric FastICA mixing and unmixing matrix estimates.