Abstract
Model selection is an important part of any statistical analysis and, indeed, is central to the pursuit of science in general. Many authors have examined the question of model selection from both frequentist and Bayesian perspectives, and many tools for selecting the “best model” have been suggested in the literature. This paper considers the various proposals from a Bayesian decision–theoretic perspective.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 279-290 |
| Number of pages | 12 |
| Journal | Journal of the American Statistical Association |
| Volume | 99 |
| Issue number | 465 |
| DOIs | |
| State | Published - Mar 1 2004 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty