glmRob.cubif {robust} | R Documentation |
Robustly fit a generalized linear model using a conditionally unbiased bounded influence estimator. This function is called by the high-level function glmRob
when method = "cubif"
(the default) is specified.
glmRob.cubif(x, y, intercept = FALSE, offset = 0, family = binomial(), null.dev = TRUE, control)
x |
a numeric model matrix. |
y |
either a numeric vector containing the response or, in the case of the binomial family, a two-column numeric matrix containing the number of successes and failures. |
intercept |
a logical value. If TRUE a column of ones is added to the design matrix. |
offset |
a numeric vector containing the offset. |
family |
a family object. |
null.dev |
a logical value. If TRUE the null deviance is computed. |
control |
a list of control parameters. See glmRob.cubif.control . |
See glmRob.object
.
Kunsch, L., Stefanski L. and Carroll, R. (1989). Conditionally Unbiased Bounded-Influence Estimation in General Regression Models, with Applications to Generalized Linear Models. JASA 84, 460-466.
Marazzi, A. (1993). Algorithms, routines and S functions for robust statistics. Wadsworth & Brooks/Cole, Pacific Grove, CA.