logdiag {HoRM} | R Documentation |
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 |
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
Examples
## 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)