5 papers
Implementation and Workflows for INLA-Based Approximate Bayesian Structural Equation Modelling
Haziq Jamil, Håvard Rue
Bayesian structural equation modelling (BSEM) offers many advantages such as principled uncertainty quantification, small-sample regularisation, and flexible model specification. H…
Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
Denis Rustand, Håvard Rue, Lisa Le Gall +1
Joint models for longitudinal and time-to-event data are increasingly used in health research to characterize the association between biomarker trajectories and the risk of clinica…
Approximate Bayesian Inference for Structural Equation Models using Integrated Nested Laplace Approximations
Haziq Jamil, Håvard Rue
Markov chain Monte Carlo (MCMC) methods remain the mainstay of Bayesian estimation of structural equation models (SEM), though they often incur a high computational cost. We presen…
A Bayesian regression framework for circular models with INLA
Xiang Ye, Janet Van Niekerk, Haavard Rue
Regression models for circular variables are less developed, since the concept of building a linear predictor from linear combinations of covariates and various random effects, bre…
Automatic cross-validation in structured models: Is it time to leave out leave-one-out?
A. Adin, E. Krainski, A. Lenzi +3
Standard techniques such as leave-one-out cross-validation (LOOCV) might not be suitable for evaluating the predictive performance of models incorporating structured random effects…