deletion.gvlma: Deletion Statistics for a Linear Model
In gvlma: Global Validation of Linear Models Assumptions

Description Usage Arguments Details Value Author(s) References See Also Examples

Computes the deletion statistics (leave-one-out) for assessing unusual observations in a linear model.

1	deletion.gvlma(gvlmaobj)

gvlmaobj

A gvlma object, as the result of a call to gvlma.

Given a gvlma object, which contains in the component GlobalTest the test statistics and p-values for the global and directional tests to assess linear models assumptions, deletion.gvlma computes the leave-one-out global and directional statistics. The deletion statistics are reported as percent relative change from the corresponding statistic value based on the full data set.

A dataframe is returned with variables DeltaGlobalStat, GStatpvalue, DeltaStat1, Stat1pvalue, DeltaStat2, Stat2pvalue, DeltaStat3, Stat3pvalue, DeltaStat4, and Stat4pvalue. Each “Delta” variable is the percent relative change in the statistic when the corresponding observation (row of the data frame) is dropped. Each “pvalue” variable is the p-value associated with the deletion statistic. (Note the p-value is NOT a change in the p-values for the full and leave-one-out statistic values.)

Slate, EH slate@stat.fsu.edu and Pena, EA pena@stat.sc.edu.

Pena, EA and Slate, EH (2006). “Global validation of linear model assumptions,” J.\ Amer.\ Statist.\ Assoc., 101(473):341-354.

gvlma

data(CarMileageData)
CarModelAssess <- gvlma(NumGallons ~ MilesLastFill, data = CarMileageData)
CarModelDel <- deletion.gvlma(CarModelAssess)
CarModelDel