Robust median estimator for generalized linear models with binary responses

Title:

Robust median estimator for generalized linear models with binary responses

Creator:

Hobza, Tomáš, Pardo, Leandro, and Vajda, Igor

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:528f46d7-06a3-44de-8265-3611313eeb19
uuid:528f46d7-06a3-44de-8265-3611313eeb19

Subject:

generalized linear models, binary responses, statistical smoothing, statistical enhancing, maximum likehood estimator, median estimator, consistency, efficiency, and robustness

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The paper investigates generalized linear models (GLM's) with binary responses such as the logistic, probit, log-log, complementary log-log, scobit and power logit models. It introduces a median estimator of the underlying structural parameters of these models based on statistically smoothed binary responses. Consistency and asymptotic normality of this estimator are proved. Examples of derivation of the asymptotic covariance matrix under the above mentioned models are presented. Finally some comments concerning a method called enhancement and robustness of median estimator are given and results of simulation experiment comparing behavior of median estimator with other robust estimators for GLM's known from the literature are reported.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[768]-794

Source:

Kybernetika | 2012 Volume:48 | Number:4

Harvested from:

CDK

Metadata only:

false