Direct fitting of dynamic models using integrated nested Laplace approximations -- INLA

DOI10.1016/j.csda.2011.10.024zbMath1368.62066OpenAlexW1997565964MaRDI QIDQ434960

Ramiro Ruiz-Cárdenas, Elias T. Krainski, Håvard Rue

Publication date: 16 July 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.10.024

zbMATH Keywords

state-space modelsLaplace approximationapproximate Bayesian inferenceaugmented modelIntegrated Nested Laplace Approximation (INLA)spatio-temporal dynamic models

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

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Uses Software

• R
• CODA
• dlm
• spdep
• GMRFLib
• INLA
• SsfPack
• KFAS
• FKF
• sspir

Cites Work

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• Approximate Bayesian inference for hierarchical Gaussian Markov random field models
• Approximate Bayesian inference for large spatial datasets using predictive process models
• Direct fitting of dynamic models using integrated nested Laplace approximations -- INLA
• Bayesian forecasting and dynamic models.
• Parameter estimation in general state-space models using particle methods
• Estimation and extrapolation of time trends in registry data -- borrowing strength from related populations
• Sensitivity analysis in Bayesian generalized linear mixed models for binary data
• Efficient simulation and integrated likelihood estimation in state space models
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Confidence Intervals for the Hyperparameters in Structural Models
• Dynamic Generalized Linear Models and Bayesian Forecasting
• Markov chain Monte Carlo in conditionally Gaussian state space models
• Markov chain Monte Carlo for dynamic generalised linear models
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• On Gibbs sampling for state space models
• Particle Markov Chain Monte Carlo Methods
• Bayesian Measures of Model Complexity and Fit
• The Effects of Seat Belt Legislation on British Road Casualties: A Case Study in Structural Time Series Modelling
• Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives