Work

Categorical Data Analysis Using a Skewed Weibull Regression Model

Year: 2018

Type: article

Abstract: 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.

Source: Entropy

DOI: 10.3390/e20030176

Authors: Renault Caron, Debajyoti Sinha, Dipak Dey, Adriano Polpo

Institutions: Universidade Federal de São Carlos, Florida State University, University of Connecticut

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funders: Conselho Nacional de Desenvolvimento Científico e Tecnológico, National Cancer Institute