A Bayesian discriminant analysis method under semiparametric density ratio models. Issue 4 (3rd April 2022)

• Record Type: Journal Article
• Authors: Wan, Shuwen; Peng, Kai
• Is Part Of: Communications in statistics. Volume 51:Issue 4(2022)
• Page Start: 1759
• Page End: 1766
• Publication Date: 2022-04-03
• Subjects: Bayesian discriminant analysis -- Density ratio model -- Semiparametric method -- Statistical simulation; 62G30 -- 62G10; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2019.1682158
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: We propose a semiparametric Bayesian discriminant analysis method. Statistical simulation shows that when the hypothesis of normal distribution is satisfied, our method is comparable to and even slightly better than the traditional method; when the hypothesis of normal distribution is not satisfied, our method is obviously better than the traditional one. We also apply our method to analyze a real data set and find that our method is better than the traditional one. Finally, we point out that implementation of our method is easy since the usual polytomous logistic regression procedures in many statistical softwares can be employed.