regrInfluential: Detecting influential cases in regression analyses

In ufs: A Collection of Utilities

Detecting influential cases in regression analyses

Description

This function combines a number of criteria for determining whether a datapoint is an influential case in a regression analysis. It then sum the criteria to compute an index of influentiality. A list of cases with an index of influentiality of 1 or more is then displayed, after which the regression analysis is repeated without those influantial cases. A scattermatrix is also displayed, showing the density curves of each variable, and in the scattermatrix, points that are colored depending on how influential each case is.

Usage

regrInfluential(formula, data, createPlot = TRUE)

## S3 method for class 'regrInfluential'
print(x, headingLevel = 3, ...)

Arguments

formula	The formule of the regression analysis.
data	The data to use for the analysis.
createPlot	Whether to create the scattermatrix (requires the GGally package to be installed).
x	Object to print.
headingLevel	The number of hash symbols to prepend to the heading.
...	Additional arguments are passed on to the regr print function.

Value

A regrInfluential object, which, if printed, shows the influential cases, the regression analyses repeated without those cases, and the scatter matrix.

Author(s)

Gjalt-Jorn Peters & Marwin Snippe

Maintainer: Gjalt-Jorn Peters [e-mail]

Examples

regrInfluential(mpg ~ hp, mtcars);

ufs documentation built on May 29, 2024, 10:30 a.m.