... model selection is consistent . This means that , if one of the entertained models is actually the true model , then Bayesian model selection will ( under very mild conditions ) guarantee selection of the true model if enough data is ...
An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
First book to synthesize the research and practice from the active field of model selection.
... model selection context. The issue of controlling the probability of wrongly choosing the null hypothesis has already initiated a considerable amount of research in ... Model Selection 6 Controlled Information Criteria for Model Selection.
... , USA xlin@hsph.harvard.edu D. B. Dunson (ed.) Random Effect and Latent Variable Model Selection, DOI: 10.1007/978-0-387-76721-5, c Springer Science+Business Media, LLC 2008 19 This chapter is organized as follows . In Sect .
... model selection in regression ) , Antoch [ 9 ] ( robust model selection with regression quantiles ) , Härdle [ 76 ] ( asymptotic optimality of AICR ) , Hurvich and Tsai [ 100 ] ( L1- regression ) , Machado [ 140 ] ( robust version of ...
... maximum expected log-likelihood, we require, for the models f j (Xn|θj0) and fk(Xn |θk0) that achieve the maximum expected log-likelihood, the log-likelihood ratio sequence 124 Bayesian model selection and statistical modeling.
... model - selection in the given situation is ; = b ; / B . These estimated selection probabilities are useful for assessing how much sampling variation there is in the selection of the best model : They directly quantify model - selection ...
... model selection ( Weisberg , 1981 and Léger and Altman , 1993 ) , the impact of model selection on inference in linear regression ( Hurvich and Tsai , 1990 ) , the use of marginal likelihood in model selection ( Shi and Tsai , 1998 ) ...
... model selection—that is, deciding to treat some parameters as equal to zero—is to make the model more understandable or easier to work with. The chapter then explores some potential risks involved in model selection and the question of ...