ufs (version 0.5.12)

regrInfluential: 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 regrInfluential print(x, headingLevel = 3, ...)

Value

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

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.

Author

Gjalt-Jorn Peters & Marwin Snippe

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

Examples

Run this code

regrInfluential(mpg ~ hp, mtcars);

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