曲阜师范大学学报（自然科学版）2024，Vol.50Issue(3)：41-48,8.DOI:10.3969/j.issn.1001-5337.2024.3.041
基于DP算法的Poisson回归模型的变量选择
Variable selection of Poisson regression models based on DP algorithm
摘要
Abstract
Using the existed DP algorithm,we optimize the likelihood function of the Poisson regression model to estimate the parameters of the model.According to the four penalty likelihood functions of the Lasso,Adaptive Lasso,SCAD and MCP,we use the DP algorithm to solve the optimization.AIC and BIC information criteria are used to select the penalty parameters.Simulation studies are conducted to verify the feasibility of the DP algorithm.Under Various indicators,the DP algorithm is compared with the existed related algorithms.关键词
Poisson回归模型/变量选择/DP算法/BIC/AICKey words
Poisson regression model/variable selection/DP algorithm/BIC/AIC分类
数理科学引用本文复制引用
王秀丽,姜喆..基于DP算法的Poisson回归模型的变量选择[J].曲阜师范大学学报（自然科学版）,2024,50(3):41-48,8.基金项目
山东省自然科学基金(ZR2020QA021). （ZR2020QA021）
