supervision: Supervision coefficients

In juscelino-izidoro/supcavs: Supervised and Unsupervised PCA Variable Selection

Description

These functions calculate coefficients that measure the influence of each predictor over the response variable to help in the supervision processes inside variable selection procedure.

Usage

standardizedRegressionCoefficient(x, y)
pearsonCoefficient(x, y)
spearmanCoefficient(x, y)
kendallCoefficient(x, y)

Arguments

x	A matrix with data. Each row is a sample and each column is a variable.
y	A vector with data corresponding to each sample of x. This is the response variable.

Value

Each function returns just one value:

standardizedRegressionCoefficient returns Standardized Regression Coefficient.

pearsonCoefficient returns Pearson Coefficient.

spearmanCoefficient returns Spearman Coefficient.

kendallCoefficient returns Kendall Coefficient.

juscelino-izidoro/supcavs documentation built on Jan. 2, 2022, 7:49 a.m.