Categorical Data Analysis Using a Skewed Weibull Regression Model

被引：5

作者：

Caron, Renault ^{[1
]}

Sinha, Debajyoti ^{[2
]}

Dey, Dipak K. ^{[3
]}

Polpo, Adriano ^{[1
]}

机构：

[1] Univ Fed Sao Carlos, Dept Stat, BR-13565905 Sao Carlos, SP, Brazil

[2] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA

[3] Univ Connecticut, Dept Stat, Storrs, CT 06269 USA

来源：

ENTROPY | 2018年 / 20卷 / 03期

关键词：

asymmetric model; binomial response; multinomial response; skewed link; Weibull distribution; BINARY; TRANSFORMATIONS; PROBIT;

D O I：

10.3390/e20030176

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in detail. The analysis of two datasets to show the efficiency of the proposed model is performed.

引用

页数：17

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