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ldstatsHD (version 1.0.1)

Linear Dependence Statistics for High-Dimensional Data

Description

Statistical methods related to the estimation and testing of multiple correlation, partial correlation and regression coefficient matrices when data is high-dimensional.

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Version

Install

install.packages('ldstatsHD')

Monthly Downloads

16

Version

1.0.1

License

GPL-3

Maintainer

Adria Caballe

Last Published

August 14th, 2017

Functions in ldstatsHD (1.0.1)

adjusted average square correlation by rows

eqCorTestByRows

Correlation matrices test by rows

equality of two correlation matrices test

One minus graph correlation matrix

Estrada Index of a graph structure

amseLambdaSelection

Augmented-MSE regularization parameter selection

aicAndbicLambdaSelection

AIC/BIC regularization parameter selection

Average square correlation by rows

AGNES coefficient

agnesLambdaSelection

AGNES regularization parameter selection

ldstatsHD-package

Linear Dependence Statistics for High-Dimensional data

Partial correlation matrix simulator plot

plot.pcorSimJoint

Joint partial correlation matrix simulator plot

Joint regression coefficient matrix estimator plot

thesholdSelection

Threshold selection for equality of correlation matrices test

pcLambdaSelection

Path Connectivity regularization parameter selection

joint estimation of multiple regression coefficient matrices

Partial Correlation Matrix simulator

pcorSimulatorJoint

joint partial correlation matrices simulator

plot.eqCorTestByRows

plot for equality of two correlation matrices by rows test

Joint partial correlation matrix estimator plot

lambdaSelection

Regularization parameter selection based on network characteristics

Internal functions

Inverse of the geodesic distance matrix

Harmonic mean of network distances

vulLambdaSelection

Vulnerability regularization parameter selection

weighted fused graphical lasso