Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior

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dc.citation.firstpage235en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleBayesian Analysisen_US
dc.citation.lastpage260en_US
dc.citation.volumeNumber19en_US
dc.contributor.authorZeng, Zijianen_US
dc.contributor.authorLi, Mengen_US
dc.contributor.authorVannucci, Marinaen_US
dc.date.accessioned2024-07-25T20:55:14Zen_US
dc.date.available2024-07-25T20:55:14Zen_US
dc.date.issued2024en_US
dc.description.abstractIn this article, we propose a novel spatial global-local spike-and-slab selection prior for image-on-scalar regression. We consider a Bayesian hierarchical Gaussian process model for image smoothing, that uses a flexible Inverse-Wishart process prior to handle within-image dependency, and propose a general global-local spatial selection prior that broadly relates to a rich class of well-studied selection priors. Unlike existing constructions, we achieve simultaneous global (i.e., at covariate-level) and local (i.e., at pixel/voxel-level) selection by introducing participation rate parameters that measure the probability for the individual covariates to affect the observed images. This along with a hard-thresholding strategy leads to dependency between selections at the two levels, introduces extra sparsity at the local level, and allows the global selection to be informed by the local selection, all in a model-based manner. We design an efficient Gibbs sampler that allows inference for large image data. We show on simulated data that parameters are interpretable and lead to efficient selection. Finally, we demonstrate performance of the proposed model by using data from the Autism Brain Imaging Data Exchange (ABIDE) study (Di Martino et al., 2014).en_US
dc.identifier.citationZeng, Z., Li, M., & Vannucci, M. (2024). Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior. Bayesian Analysis, 19(1), 235–260. https://doi.org/10.1214/22-BA1352en_US
dc.identifier.digital22-BA1352en_US
dc.identifier.doihttps://doi.org/10.1214/22-BA1352en_US
dc.identifier.urihttps://hdl.handle.net/1911/117487en_US
dc.language.isoengen_US
dc.publisherProject Eucliden_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license.  Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleBayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prioren_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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