cooks.distance.mlm: Cook's distance for a MLM

In mvinfluence: Influence Measures and Diagnostic Plots for Multivariate Linear Models

Cook's distance for a MLM

Description

The functions cooks.distance.mlm and hatvalues.mlm are designed as extractor functions for regression deletion diagnostics for multivariate linear models following Barrett & Ling (1992). These are close analogs of methods for univariate and generalized linear models handled by the influence.measures in the stats package.

Usage

## S3 method for class 'mlm'
cooks.distance(model, infl = mlm.influence(model, do.coef = FALSE), ...)

Arguments

model	A mlm object, fit by lm()
infl	A inflmlm object. The default simply runs mlm.influence() on the model, suppressing coefficients.
...	Ignored

Details

In addition, the functions provide diagnostics for deletion of subsets of observations of size m>1.

Value

A vector of Cook's distances

References

Barrett, B. E. and Ling, R. F. (1992). General Classes of Influence Measures for Multivariate Regression. Journal of the American Statistical Association, 87(417), 184-191.

Examples

data(Rohwer, package="heplots")
Rohwer2 <- subset(Rohwer, subset=group==2)
rownames(Rohwer2)<- 1:nrow(Rohwer2)
Rohwer.mod <- lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)

hatvalues(Rohwer.mod)
cooks.distance(Rohwer.mod)

mvinfluence documentation built on Sept. 21, 2022, 9:09 a.m.