Entropic criterion for model selection
| dc.creator | Tseng, Chih-Yuan | |
| dc.date | 2006-04-03 | |
| dc.date.accessioned | 2026-07-07T07:05:11Z | |
| dc.date.available | 2026-07-07T07:05:11Z | |
| dc.description | Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback-Leibler distance or relative entropy as a selection criterion. Yet that will raise two questions, why uses this criterion and are there any other criteria. Besides, conventional approaches require a reference prior, which is usually difficult to get. Following the logic of inductive inference proposed by Caticha, we show relative entropy to be a unique criterion, which requires no prior information and can be applied to different fields. We examine this criterion by considering a physical problem, simple fluids, and results are promising. | |
| dc.description | 10 pages. Accepted for publication in Physica A, 2006 | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0604027 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0604027 | |
| dc.identifier | Physica A370, 530 (2006) | |
| dc.identifier | doi:10.1016/j.physa.2006.03.024 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/109586 | |
| dc.subject | Statistical Mechanics | |
| dc.title | Entropic criterion for model selection | |
| dc.type | text |