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Categorical Data Analysis Using a Skewed Weibull Regression Model
oleh: Renault Caron, Debajyoti Sinha, Dipak K. Dey, Adriano Polpo
Format: | Article |
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Diterbitkan: | MDPI AG 2018-03-01 |
Deskripsi
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.