学术报告(田国梁 11.16)

Zero-one-inflated simplex regression models for the analysis of continuous proportion data

发布人:周妍 发布日期:2018-10-29
主题
Zero-one-inflated simplex regression models for the analysis of continuous proportion data
活动时间
-
活动地址
新数学楼416
主讲人
田国梁 教授(南方科技大学数学系)

摘要:

Continuous data restricted in the closed unit interval [0,1] often appear in various fields. Neither the beta distribution nor the simplex distribution provides a satisfactory fitting for such data, since the densities of the two distributions are defined only in the open interval (0,1). To model continuous proportional data with excessive zeros and excessive ones, it is the first time that we propose a zero-one-inflated simplex (ZOIS) distribution, which can be viewed as a mixture of the Bernoulli distribution and the simplex distribution. Besides, we introduce a new minorization-maximization (MM) algorithm to calculate the maximum likelihood estimates (MLEs) of parameters in the simplex distribution without covariates. Likelihood-based inference methods for the ZOIS regression model are also provided. Some simulation studies are performed and the hospital stay data of Barcelona in 1988 and 1990 are analyzed to illustrate the proposed methods.

 

数学学院

2018年10月29日