The Effective Sample Size
| Autor: | James O. Berger, Maria J. Bayarri, Luis R. Pericchi |
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| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | Econometric Reviews. 33:197-217 |
| ISSN: | 1532-4168 0747-4938 |
| DOI: | 10.1080/07474938.2013.807157 |
| Popis: | Model selection procedures often depend explicitly on the sample size n of the experiment. One example is the Bayesian information criterion (BIC) criterion and another is the use of Zellner–Siow priors in Bayesian model selection. Sample size is well-defined if one has i.i.d real observations, but is not well-defined for vector observations or in non-i.i.d. settings; extensions of critera such as BIC to such settings thus requires a definition of effective sample size that applies also in such cases. A definition of effective sample size that applies to fairly general linear models is proposed and illustrated in a variety of situations. The definition is also used to propose a suitable ‘scale’ for default proper priors for Bayesian model selection. |
| Databáze: | OpenAIRE |
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