Learn R Programming
⚠️There's a newer version (1.2.17) of this package.Take me there.

CorReg (version 1.1.1)

Linear Regression Based on Linear Structure Between Covariates

Description

Linear regression based on a recursive structural equation model (explicit multiples correlations) found by a MCMC algorithm. It permits to face highly correlated covariates. Variable selection is included (by lasso, elastic net, etc.). It also provides some graphical tools for basic statistics (Boxplot with confidence intervals, etc) and regression trees.

Copy Link

Version

Install

install.packages('CorReg')

Monthly Downloads

35

Version

1.1.1

License

CeCILL

Maintainer

Clement THERY

Last Published

December 9th, 2015

Functions in CorReg (1.1.1)

recursive_tree

decision tree in a recursive way
density_estimation

BIC of estimated marginal gaussian mixture densities
compare_struct

To compare sub-regression structures
structureFinder

MCMC algorithm to find a structure between the covariates
showdata

To show the missing values of a dataset
BicZ

Compute the BIC of a given structure
Terminator

Destructing values to have missing ones
matplot_zone

Matplot with curves comparison by background colors.
mixture_generator

Gaussian mixtures dataset generator with regression between the covariates
Conan

Removes missing values (rows and column to obtain a large full matrix)
correg

Linear regression using CorReg's method, with variable selection.
readZ

read the structure and explain it
MSE_loc

simple MSE function
BoxPlot

Matplot with curves comparison by background colors.
CorReg-package

Quick tutorial for CorReg package