Learn R Programming

JWileymisc (version 0.3.1)

mvqq: NOTE: this function is replaced and combined into the testdistr function.

Description

This is a simple plotting function designed to help examine multivariate normality using the (squared) Mahalanobis distance.

Usage

mvqq(dat, use = c("fiml", "pairwise.complete.obs", "complete.obs"),
  plot = TRUE)

Arguments

dat

A data frame or matrix of multivariate data to be plotted

use

A character vector indicating how the moments (means and covariance matrix) should be estimated in the presence of missing data. The default is to use full information maximum likelihood based on functions in lavaan.

plot

A logical argument whether to plot the results. Defaults to TRUE.

Value

An invisible list of the density plot, QQ plot, and the data containing quantiles from the chi-squared distribution. Can be useful to find and remove multivariate outliers.

See Also

SEMSummary

Examples

Run this code
# NOT RUN {
testdistr(mtcars, "mvnormal")

# }

Run the code above in your browser using DataLab