HoRM (version 0.1.3)

logdiag: Diagnostic Measures of Certain Regression Estimates

Description

A function for computing various residual-based and influence-based quantities from a linear regression fit using lm or a generalized linear regression fit using glm.

Usage

logdiag(out)

Arguments

out

An object of class lm or glm.

Value

logdiag returns a data frame with the following columns:

r.i

The raw residuals.

p.i

The Pearson residuals.

d.i

The deviance residuals.

stud.r.i

The Studentized raw residuals.

stud.p.i

The Studentized Pearson residuals.

stud.d.i

The Studentized deviance residuals.

h.ii

The leverage values.

C.i

The Cook's distance value.

C.i.bar

The average Cook's distance value when omitting observation i.

DFDEV

The change in the deviance statistic when omitting observation i.

DFCHI

The change in the Pearson's chi-square statistic when omitting observation i.

fit

The estimated response (fitted) values.

References

Young, D. S. (2017), Handbook of Regression Methods, CRC Press.

See Also

glm, lm

Examples

# NOT RUN {
## Diagnostic summaries for the logistic regression fit to the
## menarche dataset.

data(menarche, package = "MASS")

glm.out = glm(cbind(Menarche, Total - Menarche) ~ Age, 
              family = binomial, data = menarche)
logdiag(glm.out)

# }