CalcPsiCWS: The Psi CWS Statistic

In EricMcKinney77/distdiffR: Two-Sample Tests of Distributional Equality for Bivariate Data

The Psi CWS Statistic

Description

This statistic computes the complementary weighted squared (CWS) differences between the empirical cumulative distribution functions for the two samples. For more information, see \insertCitemckinney2022extensions;textualdistdiffR and \insertCitemckinney2021extensions;textualdistdiffR.

Usage

CalcPsiCWS(data, subjects)

Arguments

data	A two column matrix of the bivariate pooled samples
subjects	A numerical vector of sample labels (use either 1 or 2)

Value

The Psi CWS statistic

References

\insertRef

mckinney2022extensionsdistdiffR

\insertRef

mckinney2021extensionsdistdiffR

Examples

data(iris)
pooled_data <- iris[iris$Species %in% c("setosa", "virginica"), 1:2]
sample_labels <- rep(1:2, c(sum(iris$Species == "setosa"),
                            sum(iris$Species == "virginica")))

CalcPsiCWS(as.matrix(pooled_data), sample_labels)

EricMcKinney77/distdiffR documentation built on April 24, 2022, 9:03 p.m.