QDComparison-package: Modern Nonparametric Tools for Two-Sample Quantile and...

In QDComparison: Modern Nonparametric Tools for Two-Sample Quantile and Distribution Comparisons

Description

Allows practitioners to determine (i) if two univariate distributions (which can be continuous, discrete, or even mixed) are equal, (ii) how two distributions differ (shape differences, e.g., location, scale, etc.), and (iii) where two distributions differ (at which quantiles), all using nonparametric LP statistics.

Author(s)

David Jungreis, Subhadeep Mukhopadhyay

Maintainer: David Jungreis <[e-mail]>

References

Jungreis, D., (2019) "Unification of Continuous, Discrete, and Mixed Distribution Two-Sample Testing with Inferences in the Quantile Domain"

Mukhopadhyay, S., (2013) "Nonparametric Inference for High Dimensional Data,"" Ph.D. diss., Texas A&M University, College Station, Texas.

Mukhopadhyay, S. and Parzen, E. (2014), "LP Approach to Statistical Modeling", arXiv:1405.2601.

Examples

x <- c(rep(0,200),rep(1,200))
y <- c(rnorm(200,0,1),rnorm(200,1,1))
L <- LP.QDC(x,y)
L$pval

QDComparison documentation built on June 24, 2019, 9:04 a.m.