Sampling-Based Bayesian Modeling with Proper Likelihood And Prior InformationFor decades, the process modeling field is dominated by traditional methods which think from a frequentist's perspective, such as Ordinary Least Squares (OLS), Principal Component Analysis (PCA), Partial Least Squares (PLS) ...
inbothunivariate andmultivariatesettings.Properscoringrulesforquantileandintervalforecastsare alsodiscussed.WerelateproperscoringrulestoBayesfactorsandtocross-validation, andproposeanovelformofcross-validation,random-foldcross-validatedlikelihood. AcasestudyonprobabilisticweatherforecastsintheNorthAmericanPacificNorth- ...
We present the results from a monthly analysis of Markov chain models for 831 stations in the contiguous USA using long-term data and discuss the temporal and spatial variations in model order as identified using the Bayesian information criteria (BIC). The maximum likelihood estimates of the ...