Particle Swarm Stepwise (PaSS) Algorithm for Information Criterion Variable Selections
- 2015-04-28 (Tue.), 15:00 PM
- 中研院-統計所 2F 交誼廳
- 茶 會:下午14:40統計所二樓交誼廳
- Prof. Ray-Bing Chen(陳瑞彬 教授)
- 國立成功大學統計學系
Abstract
A new stochastic search algorithm is proposed for solving information-criterion-based variable selection problems. The idea behind the proposed algorithm is to search for the best model for the previously specified information criterion using multiple search particles. These particles simultaneously explore the candidate model space and communicate with each other to share search information. A new stochastic stepwise procedure is proposed to update the model during the search for the best model {by adding or deleting variables}. The proposed algorithm can also be used to generate variable selection ensembles {efficiently.} Several examples are used to demonstrate the performances of the proposed algorithm. A parallel version of the proposed algorithm is also introduced to accelerate the performance in terms of computation time.