Predictive Bayesian Model Selection
نویسندگان
چکیده
منابع مشابه
Posterior predictive Bayesian phylogenetic model selection.
We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand-Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-...
متن کاملPredictive Alternatives in Bayesian Model Selection
Predictive Alternatives in Bayesian Model Selection by Womack, Andrew Doctor of Philosophy in Mathematics, Washington University in St. Louis, May, 2011. Professor Jeff Gill, Chairperson Model comparison and hypothesis testing is an integral part of all data analyses. In this thesis, I present two new families of information criteria that can be used to perform model comparison. In Chapter 1, I...
متن کاملComparison of Bayesian predictive methods for model selection
The goal of this paper is to compare several widely used Bayesian model selection methods in practical model selection problems, highlight their differences and give recommendations about the preferred approaches. We focus on the variable subset selection for regression and classification and perform several numerical experiments using both simulated and real world data. The results show that t...
متن کاملBayesian Model Averaging and Bayesian Predictive Information Criterion for Model Selection
The problem of evaluating the goodness of the predictive distributions developed by the Bayesian model averaging approach is investigated. Considering the maximization of the posterior mean of the expected log-likelihood of the predictive distributions (Ando (2007a)), we develop the Bayesian predictive information criterion (BPIC). According to the numerical examples, we show that the posterior...
متن کاملOptimal predictive model selection
Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal l...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Journal of Mathematical and Management Sciences
سال: 2011
ISSN: 0196-6324,2325-8454
DOI: 10.1080/01966324.2011.10737798