We introduce a closed-form, refit-free procedure for leave-one-cluster-out (LOCO) cross-validation in multilevel Gaussian Bayesian structural equation models (SEMs), together with predictive scoring of every nested submodel. Conditional independence of clusters given the parameters expresses the cluster-deleted posteri...
Mohammad Alhyari, Haziq Jamil, Hans Montcho et al.· 0 citations
The log Gaussian Cox Process (LGCP) is one of the most widely used models for the analysis of spatial point patterns. Although Bayesian methods and software for fitting LGCPs are now well established, practical tools for model criticism, predictive assessment, and model comparison remain comparatively underdeveloped. T...
Hans Montcho, H. Rue, F. Lindgren et al.· 0 citations
A lightweight selector captures the sparsity pattern of the Cholesky factor and routes the matrix to one of three regimes: dense, sparse, or an intermediate semisparse regime, which achieves the lowest total factorization time in every regime.
Esmail Abdul Fattah, H. Ltaief, H. Rue et al.· 1 citation
This article proposes an innovative framework, INLA-MBN, that integrates multilevel BNs (MBNs) with the integrated nested Laplace approximation (INLA), thereby facilitating efficient structure and parameter learning in both longitudinal and cross-sectional multilevel data contexts.
B. E. Yirdaw, L. K. Debusho, J. van Niekerk et al.· Statistical Methods in Medic...· 0 citations
A distance-based prior is proposed that assigns mass decaying exponentially in the Fisher arc-length distance from a user-specified reference correlation matrix, enabling shrinkage toward any target correlation structure rather than being confined to the identity matrix.
A. Freni-Sterrantino, J. van Niekerk, E. Krainski et al.· 2 citations
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