Categorical Data Analysis Using a Skewed Weibull Regression Model
1
Department of Statistics, Federal University of São Carlos, São Carlos 13565-905, Brazil
2
Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
3
Department of Statistics, University of Connecticut, Storrs, CT 06269, USA
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(3), 176; https://doi.org/10.3390/e20030176
Received: 24 November 2017
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Revised: 14 February 2018
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Accepted: 27 February 2018
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Published: 7 March 2018
(This article belongs to the Special Issue MaxEnt 2017 - The 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering)
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.
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Keywords:
asymmetric model; binomial response; multinomial response; skewed link; Weibull distribution
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MDPI and ACS Style
Caron, R.; Sinha, D.; Dey, D.K.; Polpo, A. Categorical Data Analysis Using a Skewed Weibull Regression Model. Entropy 2018, 20, 176. https://doi.org/10.3390/e20030176
AMA Style
Caron R, Sinha D, Dey DK, Polpo A. Categorical Data Analysis Using a Skewed Weibull Regression Model. Entropy. 2018; 20(3):176. https://doi.org/10.3390/e20030176
Chicago/Turabian StyleCaron, Renault, Debajyoti Sinha, Dipak K. Dey, and Adriano Polpo. 2018. "Categorical Data Analysis Using a Skewed Weibull Regression Model" Entropy 20, no. 3: 176. https://doi.org/10.3390/e20030176
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