Variational Bayesian methods for spatial data analysis
type: Item
instance of: scholarly article
title: Variational Bayesian methods for spatial data analysis
zbMATH Open document ID: 1271.62113
author: Qian Ren
author: Andrew O. Finley
author: James S. Hodges
author: Sudipto Banerjee
published in: Computational Statistics and Data Analysis
publication date: 2013-03-14T00:00:00Z
Mathematics Subject Classification ID: 62H11
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 65C40
zbMATH DE Number: 6144935
zbMATH Keywords: Bayesian inference
zbMATH Keywords: Gaussian process
zbMATH Keywords: hierarchical models
zbMATH Keywords: Markov chain Monte Carlo
zbMATH Keywords: spatial process models
zbMATH Keywords: variational Bayesian
describes a project that uses: GMRFLib
describes a project that uses: gss
describes a project that uses: spBayes
describes a project that uses: GeoBUGS
MaRDI profile type: Publication
full work available at URL: j.csda.2011.05.021
OpenAlex ID: W2164039610
cites work: Q4441026
cites work: Gaussian Predictive Process Models for Large Spatial Data Sets
cites work: Q4217800
cites work: Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping
cites work: Q3125703
cites work: Q4256209
cites work: Bayesian multivariate process modeling for prediction of forest attributes
cites work: Approximate Likelihood for Large Irregularly Spaced Spatial Data
cites work: Q5332396
cites work: Model choice: a minimum posterior predictive loss approach
cites work: Spatial Modeling With Spatially Varying Coefficient Processes
cites work: Nonstationary multivariate process modeling through spatially varying coregionalization
cites work: Q5456605
cites work: An introduction to variational methods for graphical models
cites work: Geoadditive Models
cites work: Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV.
cites work: Q4457477
cites work: Q4217799
cites work: Computational techniques for spatial logistic regression with large data sets
cites work: Gaussian Markov Random Fields
cites work: Fitting Gaussian Markov Random Fields to Gaussian Fields
cites work: Bayesian Measures of Model Complexity and Fit
cites work: Interpolation of spatial data. Some theory for kriging
cites work: Approximating Likelihoods for Large Spatial Data Sets
cites work: Q4406162
cites work: A dimension-reduced approach to space-time Kalman filtering
DOI: 10.1016/J.CSDA.2011.05.021
description: scientific article; zbMATH DE number 6144935