On connectivity of fibers with positive marginals in multiple logistic regression |
| |
Authors: | Hisayuki Hara Akimichi Takemura Ruriko Yoshida |
| |
Affiliation: | a Department of Technology Management for Innovation, University of Tokyo, 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656, Japan b Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656, Japan c CREST, JST, Japan d Department of Statistics, University of Kentucky, Lexington KY 40506, USA |
| |
Abstract: | In this paper we consider exact tests of a multiple logistic regression with categorical covariates via Markov bases. In many applications of multiple logistic regression, the sample size is positive for each combination of levels of the covariates. In this case we do not need a whole Markov basis, which guarantees connectivity of all fibers. We first give an explicit Markov basis for multiple Poisson regression. By the Lawrence lifting of this basis, in the case of bivariate logistic regression, we show a simple subset of the Markov basis which connects all fibers with a positive sample size for each combination of levels of covariates. |
| |
Keywords: | 62H17 62H15 |
本文献已被 ScienceDirect 等数据库收录! |
|