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, Håvard Rue, F. Lindgren et al.· 0 citations
Sparse direct Cholesky solvers fix one data structure for an entire matrix, but symmetric positive definite systems range from nearly dense to irregular, sometimes mixing both within one matrix. We let the data structure follow the sparsity structure, across matrices and across tiles within a matrix. Before numerical w...
Esmail Abdul Fattah, H. Ltaief, Håvard Rue et al.· 0 citations
Bayesian networks (BNs) are widely used tools for the modeling of complex dependencies among variables. However, their application to multilevel or clustered data remains constrained, especially in scenarios involving multiple random effects, due to a lack of methods and more pressing, efficient computational framework...
B. E. Yirdaw, L. K. Debusho, J. van Niekerk et al.· Statistical Methods in Medic...· 0 citations
Specifying a prior over the space of correlation matrices is a persistent challenge in Bayesian analysis. The space is a curved manifold whose dimension grows quadratically with the number of variables, making substantive prior beliefs difficult to encode.\\ We propose a distance-based prior that assigns mass decaying...
A. Freni-Sterrantino, J. V. Niekerk, E. Krainski et al.· 1 citation
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