logregWBY {RobStatTM}

Bianco and Yohai estimator for logistic regression

Description

This function computes the weighted M-estimator of Bianco and Yohai in logistic regression. By default, an intercept term is included and p parameters are estimated. Modified by Yohai (2018) to take as initial estimator a weighted ML estimator computed with weights derived from the MCD estimator of the continuous explanatory variables. The same weights are used to compute the final weighted M-estimator. For more details we refer to Croux, C., and Haesbroeck, G. (2002), "Implementing the Bianco and Yohai estimator for Logistic Regression"

Usage

logregWBY(x0, y, intercept = 1, const = 0.5, kmax = 1000, maxhalf = 10)

Arguments

x0

matrix of explanatory variables;

y

vector of binomial responses (0 or 1);

intercept

1 or 0 indicating if an intercept is included or or not

const

tuning constant used in the computation of the estimator (default=0.5);

kmax

maximum number of iterations before convergence (default=1000);

maxhalf

max number of step-halving (default=10).

Value

A list with the following components:

coefficients

estimates for the regression coefficients

standard.deviation

standard deviations of the coefficients

fitted.values

fitted values

residual.deviances

residual deviances

components

logical value indicating whether convergence was achieved

objective

value of the objective function at the minimum

Author(s)

Christophe Croux, Gentiane Haesbroeck, Victor Yohai

References

http://www.wiley.com/go/maronna/robust

Examples

data(skin)
Xskin <- as.matrix( skin[, 1:2] )
yskin <- skin$vasoconst
skinWBY <- logregWBY(Xskin, yskin, intercept=1)
skinWBY$coeff
skinWBY$standard.deviation