chisqPlot: Chi-Squared Plot for Outlier Detection

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

This plots the robust Mahalanobis distances from a robust estimate of multivariate location and covariance against the theoretical Chi-squared quantiles for a matrix with p dimensions. This functions analagously to the univariate qqplot.

Usage

chisqPlot(x, rmu, rcov, alpha = 0.975)

Arguments

x	a data frame or matrix of numeric covariates
rmu	robust multivariate center
rcov	robust covariance matrix
alpha	quantile of chi-squared distribution for declaring outliers. defaults to 0.975

Value

a plot

Examples

out <- cov.ogk(x, all = T)
chisqPlot(x, out$center, out$cov)

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.