Residuals of Robust Generalized Linear Model Fits
Compute residuals of a fitted glmrob model, i.e., robust
generalized linear model fit.
## S3 method for class 'glmrob'
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 in glm 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.
The residuals (S3) method (see methods) for
glmrob models has been modeled to follow closely the
method for classical (non-robust) glm fitted models.
Possibly, see its documentation, i.e., residuals.glm, for
further details.
See those for the classical GLM's, glm.
glmrob for computing object, anova.glmrob;
the corresponding generic functions, summary.glmrob,
coef,
fitted,
residuals.
### -------- Gamma family -- data from example(glm) ---
clotting <- data.frame(
u = c(5,10,15,20,30,40,60,80,100),
lot1 = c(118,58,42,35,27,25,21,19,18),
lot2 = c(69,35,26,21,18,16,13,12,12))
summary(cl <- glm (lot1 ~ log(u), data=clotting, family=Gamma))
summary(ro <- glmrob(lot1 ~ log(u), data=clotting, family=Gamma))
clotM5.high <- within(clotting, { lot1[5] <- 60 })
cl5.high <- glm (lot1 ~ log(u), data=clotM5.high, family=Gamma)
ro5.high <- glmrob(lot1 ~ log(u), data=clotM5.high, family=Gamma)
rr <- range(residuals(ro), residuals(cl), residuals(ro5.high))
plot(residuals(ro5.high) ~ residuals(cl5.high), xlim = rr, ylim = rr, asp = 1)
abline(0,1, col=2, lty=3)
points(residuals(ro) ~ residuals(cl), col = "gray", pch=3)
## Show all kinds of residuals:
r.types <- c("deviance", "pearson", "working", "response")
sapply(r.types, residuals, object = ro5.high)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.