155 citations · 296 across the 33 of their papers we have counts for
40 papers
Beyond Laplace: Closed-form wrapped Gaussian posterior approximations on statistical manifolds
Marcelo Hartmann, Luu Hoang Phuc Hau, Anton Mallasto +5
In Bayesian statistics, the Laplace approximation provides a computationally efficient approximation to posterior distributions. However, its Gaussian form restricts it to elliptic…
Spatially continuous modelling of aggregated outcome data
Stephen Jun Villejo, Peter Diggle, Finn Lindgren +5
This work develops a block aggregation approach to spatial estimation and prediction when the response is observed at a coarse spatial scale, for example as counts of events in adm…
Bayesian identification of early warning signals for long-range dependent climatic time series
Sigrunn H. Sørbye, Eirik Myrvoll-Nilsen, Håvard Rue
Detecting early warning signals in climatic time series is essential for anticipating critical transitions and tipping points. Common statistical indicators include increased varia…
A new approach for Bayesian joint modeling of longitudinal and cure-survival outcomes using the defective Gompertz distribution
Dionisio Silva Neto, Denis Rustand, Haavard Rue +2
In recent medical studies, the combination of longitudinal measurements with time-to-event data has increased the demand for more sophisticated models without unbiased estimates. J…
Bayesian models for missing and misclassified variables using integrated nested Laplace approximations
Emma Skarstein, Leonardo Soares Bastos, Håvard Rue +1
Misclassified variables used in regression models, either as a covariate or as the response, may lead to biased estimators and incorrect inference. Even though Bayesian models to a…
inlabru: software for fitting latent Gaussian models with non-linear predictors
Finn Lindgren, Fabian Bachl, Janine Illian +3
The integrated nested Laplace approximation (INLA) method has become a popular approach for computationally efficient approximate Bayesian computation. In particular, by leveraging…