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Showing 1 to 4 of 4 for “"fractional bayes"”.
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Bayesian Model Selection for Spatial Data and Cost-constrained Applications
Bayesian model selection is a useful tool for identifying an appropriate model class, dependence structure, and valuable predictors for a wide variety of applications. In this work we consider objective Bayesian model selection where no subjective information is available to inform priors on model …
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Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection
… given the observed data. Specifically, we offer Bayesian model selection-based approaches to reveal latent group-based heteroscedasticity, regression effects, and/or interactions. Failure to account for such structures can produce misleading conclusions. Since the presence of latent group …
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Objective bayesian variable selection for censored data
… and observations are right censored. Under a Bayesian approach, the most widely used tools are the Bayes Factors (BFs) which are, however, undefined when using improper priors. Some commonly used tools in literature, which solve the problem of indeterminacy in model selection, are the …
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Off- and online detection of dynamical phases in time series
… sequently. Application of so-called objective Bayes techniques provide a change point detection procedure which is (i) sampling free, as all needed integrals can be solved analytically, (ii) applicable to high-dimensional time series and (iii) computationally cheap. It turns out, that the …