A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets
From MaRDI portal
Publication:6631117
DOI10.1080/00401706.2022.2115558MaRDI QIDQ6631117
Publication date: 31 October 2024
Published in: Technometrics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- A comparison of spatial predictors when datasets could be very large
- Nonstationary modeling for multivariate spatial processes
- Local likelihood estimation for nonstationary random fields
- Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
- Hierarchical nonlinear spatio-temporal agent-based models for collective animal movement
- Computationally efficient multivariate spatio-temporal models for high-dimensional count-valued data (with discussion)
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- A Computationally Efficient Projection-Based Approach for Spatial Generalized Linear Mixed Models
- Interpolation of nonstationary air pollution processes: a spatial spectral approach
- Multiresolution models for nonstationary spatial covariance functions
- Bayesian Wombling
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Computer Model Calibration Using High-Dimensional Output
- Model-Based Geostatistics
- On the Early History of the Singular Value Decomposition
- Spatial Modeling With Spatially Varying Coefficient Processes
- Robust and Scalable Bayes via a Median of Subset Posterior Measures
- Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models
- Bayesian Hierarchical Models With Conjugate Full-Conditional Distributions for Dependent Data From the Natural Exponential Family
- Efficient Estimation of Non-stationary Spatial Covariance Functions with Application to High-resolution Climate Model Emulation
- Statistics for Spatial Data
- Statistical Agent-Based Models for Discrete Spatio-Temporal Systems
- Efficient Gaussian process regression for large datasets
- Analyzing Nonstationary Spatial Data Using Piecewise Gaussian Processes
- A review of Bayesian variable selection methods: what, how and which
- Bayesian nonstationary spatial modeling for very large datasets
- The Elements of Statistical Learning
- Spatial data fusion for large non-Gaussian remote sensing datasets
- Spatial modeling with R-INLA: a review
- Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets
- Estimation and inference in spatially varying coefficient models
- PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models
This page was built for publication: A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets