glm.summaries {stats} | R Documentation |
These functions are all methods
for class glm
or
summary.glm
objects.
## S3 method for class 'glm' family(object, ...) ## S3 method for class 'glm' residuals(object, type = c("deviance", "pearson", "working", "response", "partial"), ...)
object |
an object of class |
type |
the type of residuals which should be returned.
The alternatives are: |
... |
further arguments passed to or from other methods. |
The references define the types of residuals: Davison & Snell is a good reference for the usages of each.
The partial residuals are a matrix of working residuals, with each column formed by omitting a term from the model.
How residuals
treats cases with missing values in the original
fit is determined by the na.action
argument of that fit.
If na.action = na.omit
omitted cases will not appear in the
residuals, whereas if na.action = na.exclude
they will appear,
with residual value NA
. See also naresid
.
For fits done with y = FALSE
the response values are computed
from other components.
Davison, A. C. and Snell, E. J. (1991) Residuals and diagnostics. In: Statistical Theory and Modelling. In Honour of Sir David Cox, FRS, eds. Hinkley, D. V., Reid, N. and Snell, E. J., Chapman & Hall.
Hastie, T. J. and Pregibon, D. (1992) Generalized linear models. Chapter 6 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
McCullagh P. and Nelder, J. A. (1989) Generalized Linear Models. London: Chapman and Hall.
glm
for computing glm.obj
, anova.glm
;
the corresponding generic functions, summary.glm
,
coef
, deviance
,
df.residual
,
effects
, fitted
,
residuals
.
influence.measures for deletion diagnostics, including
standardized (rstandard
)
and studentized (rstudent
) residuals.