R: Robust GLM CUBIF Fitter

glmRob.cubif {robust} | R Documentation

## 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)

### 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`.

### Value

See `glmRob.object`.

### 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`.

[Package robust version 0.4-18.1 Index]