multReg: Diagnostics for Linear Regression

In USGS-R/smwrStats: R functions to support statistical methods in water resources

Diagnostics for Linear Regression

Description

Computes diagnostics for linear regression.

Usage

multReg(object)

Arguments

object

the linear regression model object

Value

A object of class "multReg" having the following components:

aovtab	the analysis of variance table, using the type II sum of squares. See Note.
parmests	a summary of object.
vif	a named vector of variance inflation factors.
diagstats	a data.frame containing the observed values, predicted values, residuals, standardized residuals, studentized residuals, leverage, Cook's D, and dfits for each observation.
crit.val	a named vector of the critical values for leverage, Cook's D, and dfits. See Note
flagobs	a logical vector indicating which observations exceeded at least one of the critical values.
object	the lm object.
x	the model matrix of explanatory variables.

Note

The type II sum of squares are calculated according to the principle of marginality, testing each term after all others, except ignoring the term's higher-order relatives. This type sum of squares is useful for assessing the overall marginal effect of each term in the model.

The critical values for the test criteria are computed as: leverage, 3p/n; Cook's D, median quantile for the F distribution with p+1 and n-p degrees of freedom; and dfits, the .01 quantile of the grubbs distribution for n observations time the square root of (p/n), where p is the number of parameters estimated in the regression and n is the number of observations.

Objects of class "multReg" have print and plot methods.

References

Draper, N.R. and Smith, H., 1998, Applied Regression Analysis, (3rd ed.): New York, Wiley, 724 p.

See Also

lm, plot.multReg,

USGS-R/smwrStats documentation built on Oct. 11, 2022, 6:15 a.m.