threeOuts: Combine All Three Common Outlier Types

In MichaelJMahometa/SDSRegressionR: Helper functions for Applied Regression Analysis

Description

Simple function to produce a plots and a final data frame from studentized deleted residuals, hat values (leverage), and Cook's distance, after a model run in lm(). Resulting dataframe will be sorted by the inThree variable (observation is considered an outlier on all three plots) and then the Cooks_D variable.

Usage

threeOuts(obj, key.variable = NULL, print.plot = FALSE)

Arguments

obj	Model object from an lm() fiitted equation.
key.variable	Required if lm() data object is of tibble class. Name of the unique key variable (identifier variable). If data object is of data.frame class, this is optional and row.names will be used instead.
print.plots	Logical: Should plots for all three outlier tests be shown?

See Also

studResidPlot levPlot cooksPlot

Examples

mod <- lm(hp ~ disp, data=mtcars)
summary(mod)
threeOuts(mod)

MichaelJMahometa/SDSRegressionR documentation built on March 3, 2021, 10:51 p.m.