Maximize 发表于 2025-3-28 16:14:34
,Power-Expected-Posterior Methodology with Baseline Shrinkage Priors,rior is updated using imaginary data. This work focuses on normal regression models when the number of observations . is smaller than the number of explanatory variables .. We introduce the PEP prior methodology using different baseline shrinkage priors and we perform some comparisons in simulated data sets.爱哭 发表于 2025-3-28 21:33:31
,Bayesian Nonparametric Scalar-on-Image Regression via Potts-Gibbs Random Partition Models,ocess is spatially dependent, thereby encouraging groups representing spatially contiguous regions. In addition, Bayesian shrinkage priors are utilised to identify the covariates and regions that are most relevant for the prediction. The proposed model is illustrated using the simulated data sets.新娘 发表于 2025-3-29 00:22:42
,A Bayesian Nonparametric Test for Cross-Group Differences Relative to a Control,up distributions are modeled in a flexible way using a dependent Dirichlet process. Monte Carlo experiments suggest that our proposal performs better than state-of-the-art frequentist alternatives for small sample sizes.性满足 发表于 2025-3-29 06:09:40
http://reply.papertrans.cn/67/6653/665259/665259_44.png预知 发表于 2025-3-29 08:53:09
http://reply.papertrans.cn/67/6653/665259/665259_45.png夸张 发表于 2025-3-29 11:38:52
,Block Structured Graph Priors in Gaussian Graphical Models,arlo Markov chain that avoids any . normalizing constant calculation when comparing graphical models. The novelty of this procedure is that it looks for block structured graphs, hence proposing moves that add or remove not just a single link but an entire group of them.半导体 发表于 2025-3-29 17:19:02
http://reply.papertrans.cn/67/6653/665259/665259_47.pngNarcissist 发表于 2025-3-29 20:08:02
http://reply.papertrans.cn/67/6653/665259/665259_48.png讽刺滑稽戏剧 发表于 2025-3-30 01:17:51
Conference proceedings 2022The book is intended for a broad audience of people interested in statistics, and provides a series of stimulating contributions on theoretical, methodological, and computational aspects of Bayesian statistics..