A New Family of BAN Estimators for Polytomous Logistic Regression Models based on ϕ- Divergence Measures

A. K. Gupta (), D. Kasturiratna, T. Nguyen and L. Pardo
Additional contact information
A. K. Gupta: Bowling Green State University
D. Kasturiratna: Bowling Green State University
T. Nguyen: Bowling Green State University
L. Pardo: Complutense University of Madrid

Statistical Methods & Applications, 2006, vol. 15, issue 2, No 3, 159-176

Abstract: Abstract In this paper we study polytomous logistic regression model and the asymptotic properties of the minimum ϕ-divergence estimators for this model. A simulation study is conducted to analyze the behavior of these estimators as function of the power-divergence measure ϕ(λ)

Keywords: Multinomial sampling; Kullback–Leibler divergence measure; Minimum ϕ-divergence estimator; Polytomous regression model; Primary 62H15; Secondary 62H17 (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10260-006-0008-6

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