Caron Renault, Sinha Debajyoti, Dey Dipak K, Polpo Adriano
Department of Statistics, Federal University of São Carlos, São Carlos 13565-905, Brazil.
Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.
Entropy (Basel). 2018 Mar 7;20(3):176. doi: 10.3390/e20030176.
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.
在本文中，我们针对由二项式模型和多项式模型产生的分类响应数据，提出了一种威布尔链接（偏态）模型。我们表明，对于此类分类数据，最常用的模型（逻辑斯蒂、概率单位和互补对数-对数模型）可以作为极限情况得到。我们进一步将所提出的模型与其他一些非对称模型进行比较。详细介绍了二项式和多项式数据响应的贝叶斯估计程序以及频率主义估计程序。对两个数据集进行了分析，以展示所提出模型的有效性。
