Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/72960
Title: | Objective Bayesian model choice for non-nested families: the case of the Poisson and the negative binomial | Authors: | Moreno, Elías Martínez, Carmen Vázquez Polo, Francisco José |
UNESCO Clasification: | 530204 Estadística económica | Keywords: | Bayesian Model Selection Consistency Rate Of Convergence Sampling Behavior For Small Sample Sizes Test For Separate Families |
Issue Date: | 2021 | Journal: | Test | Abstract: | Selecting a statistical model from a set of competing models is a central issue in the scientific task, and the Bayesian approach to model selection is based on the posterior model distribution, a quantification of the updated uncertainty on the entertained models. We present a Bayesian procedure for choosing a family between the Poisson and the geometric families and prove that the procedure is consistent with rate O(an) , a> 1 , where a is a function of the parameter of the true model. An extension of this procedure to the multiple testing Poisson and negative binomial with r successes for r= 1 , … , L is also proved to be consistent with exponential rate. For small sample sizes, a simulation study indicates that the model selection between the above distributions is made with large uncertainty when sampling from a specific subset of distributions. This difficulty is however mitigated by the large consistency rate of the procedure. | URI: | http://hdl.handle.net/10553/72960 | ISSN: | 1133-0686 | DOI: | 10.1007/s11749-020-00717-z | Source: | Test[ISSN 1133-0686], n. 30, p. 255–273 |
Appears in Collections: | Artículos |
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.