Spatially varying dynamic coefficient models
From MaRDI portal
Publication:2474388
DOI10.1016/j.jspi.2007.03.060zbMath1130.62095OpenAlexW1994822253MaRDI QIDQ2474388
Esther Salazar, Marina Silva Paez, Dani Gamerman, Flávia M. P. F. Landim
Publication date: 6 March 2008
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2007.03.060
Inference from spatial processes (62M30) Linear regression; mixed models (62J05) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)
Related Items (3)
Bayesian modeling of discrete-time point-referenced spatio-temporal data ⋮ Spatially varying dynamic coefficient models ⋮ Bayesian latent structure models with space-time dependent covariates
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bayesian forecasting and dynamic models.
- Spatial variation. 2nd ed
- The kriged Kalman filter. (With discussion)
- Dynamic hierarchical models: an extension to matrix-variate observations.
- Spatially varying dynamic coefficient models
- Dynamic Models for Spatiotemporal Data
- A Spatiotemporal Model for Mexico City Ozone Levels
- Some matrix-variate distribution theory: Notational considerations and a Bayesian application
- Venezuelan Rainfall Data Analysed by Using a Bayesian Space–time Model
- DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
- On Gibbs sampling for state space models
- Objective Bayesian Analysis of Spatially Correlated Data
- Spatial Modeling With Spatially Varying Coefficient Processes
- A dimension-reduced approach to space-time Kalman filtering
- Equation of State Calculations by Fast Computing Machines
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- Monte Carlo sampling methods using Markov chains and their applications
This page was built for publication: Spatially varying dynamic coefficient models