Bayesian evidence and model selection
نویسندگان
چکیده
منابع مشابه
Bayesian Fuzzy Regression Analysis and Model Selection: Theory and Evidence
In this study we suggest a Bayesian approach to fuzzy clustering analysis – the Bayesian fuzzy regression. Bayesian Posterior Odds analysis is employed to select the correct number of clusters for the fuzzy regression analysis. In this study, we use a natural conjugate prior for the parameters, and we find that the Bayesian Posterior Odds provide a very powerful tool for choosing the number of ...
متن کاملBayesian Model Selection
Traditionally, Bayes factors, posterior odds and posterior model probabilities are used in Bayesian model selection. This approach has, however, the problem that the conclusions are often too sensitive to prior specifications. Another approach is to use discrepancy measures in model comparison and posterior predictive checks in the assesment of model adequecy. These approaches are briefly summa...
متن کاملRobust Bayesian Model Selection
This paper extends the robust Bayesian inference in misspeci ed models of Müller (2013, Econometrica) to Bayesian model selection of a set of misspeci ed models. It is shown that when a model is misspeci ed, under the Kullback-Leibler loss function, the risk associated with Müllers posterior is less (weakly) than that with the original posterior distribution asymptotically. Based on this new r...
متن کاملBayesian Model Averaging , Learning and Model Selection ∗
Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecastin...
متن کاملBayesian Model Selection and Model Averaging.
This paper reviews the Bayesian approach to model selection and model averaging. In this review, I emphasize objective Bayesian methods based on noninformative priors. I will also discuss implementation details, approximations, and relationships to other methods. Copyright 2000 Academic Press.
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: Digital Signal Processing
سال: 2015
ISSN: 1051-2004
DOI: 10.1016/j.dsp.2015.06.012