| deletion.gvlma {gvlma} | R Documentation |
Deletion Statistics for a Linear Model
Description
Computes the deletion statistics (leave-one-out) for assessing unusual observations in a linear model.
Usage
deletion.gvlma(gvlmaobj)
Arguments
gvlmaobj |
A |
Details
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.
Value
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.)
Author(s)
Slate, EH slate@stat.fsu.edu and Pena, EA pena@stat.sc.edu.
References
Pena, EA and Slate, EH (2006). “Global validation of linear model assumptions,” J.\ Amer.\ Statist.\ Assoc., 101(473):341-354.
See Also
Examples
data(CarMileageData)
CarModelAssess <- gvlma(NumGallons ~ MilesLastFill, data = CarMileageData)
CarModelDel <- deletion.gvlma(CarModelAssess)
CarModelDel