Second Order Admissibilities in Multi-parameter Logistic Regression Model
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Second Order Admissibilities in Multi-parameter Logistic Regression Model

Authors: Chie Obayashi, Hidekazu Tanaka, Yoshiji Takagi

Abstract:

In multi-parameter family of distributions, conditions for a modified maximum likelihood estimator to be second order admissible are given. Applying these results to the multi-parameter logistic regression model, it is shown that the maximum likelihood estimator is always second order inadmissible. Also, conditions for the Berkson estimator to be second order admissible are given.

Keywords: Berkson estimator, modified maximum likelihood estimator, Multi-parameter logistic regression model, second order admissibility.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1062872

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References:


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[4] H. Tanaka, C. Obayashi and Y. Takagi, "On second order admissibilities in two-parameter logistic regression model," submitted for publication.
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