Spatio-temporal hierarchical Bayesian analysis of wildfires with Stochastic Partial Differential Equations. A case study from Valencian Community (Spain)
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Publication:5037069
DOI10.1080/02664763.2019.1661360OpenAlexW2971836520WikidataQ117713855 ScholiaQ117713855MaRDI QIDQ5037069
Publication date: 25 February 2022
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10234/184360
Uses Software
Cites Work
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- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Point process modeling of wildfire hazard in Los Angeles county, California
- Bayesian computing with INLA: new features
- Spatio-temporal modeling of particulate matter concentration through the SPDE approach
- Bayesian spatio-temporal prediction of cancer dynamics
- Going off grid: computationally efficient inference for log-Gaussian Cox processes
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Structured Spatio-Temporal Shot-Noise Cox Point Process Models, with a View to Modelling Forest Fires
- Bayesian Measures of Model Complexity and Fit
- Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
- Spatial and Spatio‐temporal Bayesian Models with R‐INLA
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