5 papers
Implementation and Workflows for INLA-Based Approximate Bayesian Structural Equation Modelling
Haziq Jamil, HÃ¥vard Rue
Bayesian structural equation modelling (BSEM) offers many advantages such as principled uncertainty quantification, small-sample regularisation, and flexible model specification. H…
Approximate Bayesian Inference for Structural Equation Models using Integrated Nested Laplace Approximations
Haziq Jamil, HÃ¥vard 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…
Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
Denis Rustand, HÃ¥vard 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…
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…
Leave-group-out cross-validation for latent Gaussian models
Zhedong Liu, Janet Van Niekerk, Haavard Rue
Evaluating the predictive performance of a statistical model is commonly done using cross-validation. Among the various methods, leave-one-out cross-validation (LOOCV) is frequentl…