robust (version 0.7-5)

glmRob.cubif: Robust GLM CUBIF Fitter

Description

Robustly fit a generalized linear model using a conditionally unbiased bounded influence (“cubif”) estimator. This function is called by the high-level function glmRob when method = "cubif" (the default) is specified.

Usage

glmRob.cubif(x, y, intercept = FALSE, offset = 0,
        family = binomial(), null.dev = TRUE, control)

Value

See glmRob.object.

Arguments

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.

References

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.

See Also

glmRob, glmRob.cubif.control.