Practical likelihood analysis for spatial generalized linear mixed models

Related Items (2)

Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models ⋮ Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering

Cites Work

Unnamed Item
An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
Approximate Bayesian inference for hierarchical Gaussian Markov random field models
Approximate Bayesian inference for large spatial datasets using predictive process models
An extended random-effects approach to modeling repeated, overdispersed count data
Model-based geostatistics.
A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models
Approximate Bayesian inference in spatial GLMM with skew normal latent variables
Pairwise likelihood inference in spatial generalized linear mixed models
Spatial statistics and computational methods
Estimation and prediction for spatial generalized linear mixed models using high order Laplace approximation
Models for discrete longitudinal data.
Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
Likelihood Inference for Spatial Generalized Linear Mixed Models
Maximum Likelihood Estimation and Inference
On Estimation and Prediction for Spatial Generalized Linear Mixed Models
Bayesian Prediction of Spatial Count Data Using Generalized Linear Mixed Models
Fixed Rank Kriging for Very Large Spatial Data Sets
Accurate Approximations for Posterior Moments and Marginal Densities
Model-Based Geostatistics
Bias Correction in Generalized Linear Mixed Models With Multiple Components of Dispersion
Maximum Likelihood Algorithms for Generalized Linear Mixed Models
A Composite Likelihood Approach to Binary Spatial Data
Approximate Inference in Generalized Linear Mixed Models
Bias correction in generalised linear mixed models with a single component of dispersion
Estimability and Likelihood Inference for Generalized Linear Mixed Models Using Data Cloning
Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets

This page was built for publication: Practical likelihood analysis for spatial generalized linear mixed models