edu.ucar.opensky::articles:17111 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-26T14:55:35.873670 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7ks6stw Bayesian functional ANOVA modeling using Gaussian process prior distributions 2010-02-05T00:00:00Z publication https://n2t.org/ark:/85065/d7ks6stw https://doi.org/10.1214/10-BA505 Kaufman, C. author Sain, Stephan R. author UCAR/NCAR - Library publisher Functional analysis of variance (ANOVA) models partition a functional response according to the main effects and interactions of various factors. This article develops a general framework for functional ANOVA modeling from a Bayesian viewpoint, assigning Gaussian process prior distributions to each batch of functional effects. We discuss the choices to be made in specifying such a model, advocating the treatment of levels within a given factor as dependent but exchangeable quantities, and we suggest weakly informative prior distributions for higher level parameters that may be appropriate in many situations. We discuss computationally efficient strategies for posterior sampling using Markov Chain Monte Carlo algorithms, and we emphasize useful graphical summaries based on the posterior distribution of model-based analogues of traditional ANOVA decompositions of variance. We illustrate this process of model specification, posterior sampling, and graphical posterior summaries in two examples. The first considers the effect of geographic region on the temperature profiles at weather stations in Canada. The second example examines sources of variability in the output of regional climate models from a designed experiment. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2010 Author(s). Published under license in Bayesian Analysis by the International Society for Bayesian Analysis. None eng geoscientificInformation