4 citations · 4 across the 5 of their papers we have counts for
5 papers
Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model
Stephen Jun Villejo, Sara Martino, Janine Illian
Dengue is an infectious disease which poses significant socioeconomic and disease burden in many tropical and subtropical regions of the world. This work aims to provide additional…
Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration
Stephen Jun Villejo, Sara Martino, Janine Illian +2
This work tackles the problem of uncertainty propagation in two-stage Bayesian models, with a focus on spatial applications. A two-stage modeling framework has the advantage of bei…
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…
A Data Fusion Model for Meteorological Data using the INLA-SPDE method
Stephen Jun Villejo, Sara Martino, Finn Lindgren +1
This work aims to combine two primary meteorological data sources in the Philippines: data from a sparse network of weather stations and outcomes of a numerical weather prediction…
Spatio-temporal Occupancy Models with INLA
Jafet Belmont, Sara Martino, Janine Illian +1
Modern methods for quantifying and predicting species distribution play a crucial part in biodiversity conservation. Occupancy models are a popular choice for analyzing species occ…