Resource title

Response smoothing estimators in binary regression

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Resource description

A shrinkage type estimator is introduced which has favorable properties in binary regression. Although binary observations are never very far away from the underlying probability, in all interesting cases there is a non-zero distance between observation and underlying mean. The proposed response smoothing estimate is based on a smoothed version of the observed responses which is obtained by shifting the observation slightly towards the mean of the observations and therefore closer to the underlying probability. Estimates of this type are very easily computed by using common program packages and exist also when the number of predictors is very large. Moreover, they are robust against outliers. A combination of response smoothing estimators and Pregibon's resistant fitting procedure corrects for the overprediciton of the resistant fitting in a very simple way. Estimators are compared in simulation studies and applications.

Resource author

Gerhard Tutz

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/23876

Resource license

Adapt according to the presented license agreement and reference the original author.