Multi-scale Vecchia approximations of Gaussian processes
From MaRDI portal
Publication:2102959
DOI10.1007/s13253-022-00488-0OpenAlexW4210948218WikidataQ114220110 ScholiaQ114220110MaRDI QIDQ2102959
Matthias Katzfuss, Jingjie Zhang
Publication date: 12 December 2022
Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13253-022-00488-0
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
- Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors
- Fixed-domain asymptotic properties of tapered maximum likelihood estimators
- Composite Gaussian process models for emulating expensive functions
- A case study competition among methods for analyzing large spatial data
- Multiscale modeling. A Bayesian perspective
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Combining Incompatible Spatial Data
- A dimension-reduced approach to space-time Kalman filtering
- A class of multi-resolution approximations for large spatial datasets
- Sparse Cholesky Factorization by Kullback--Leibler Minimization
- Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets
- Spatio‐temporal smoothing and EM estimation for massive remote‐sensing data sets
- A Fast, Optimal Spatial-Prediction Method for Massive Datasets
- Multi-scale and hidden resolution time series models
- A general framework for Vecchia approximations of Gaussian processes
This page was built for publication: Multi-scale Vecchia approximations of Gaussian processes
