scientific article; zbMATH DE number 7625170
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Michele Peruzzi, David B. Dunson
Publication date: 29 November 2022
Full work available at URL: https://arxiv.org/abs/2012.00943
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gaussian processMarkov chain Monte Carlodirected acyclic graphgeostatisticsmultivariate regressionmultiscale/multiresolution
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- BART: Bayesian additive regression trees
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Robust adaptive Metropolis algorithm with coerced acceptance rate
- Efficient Algorithms for Bayesian Nearest Neighbor Gaussian Processes
- GitHub
- Cross-covariance functions for multivariate geostatistics
- RcppArmadillo: accelerating R with high-performance C++ linear algebra
- High-dimensional Bayesian geostatistics
- Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
- A case study competition among methods for analyzing large spatial data
- Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis
- Multiscale modeling. A Bayesian perspective
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
- Hierarchical Low Rank Approximation of Likelihoods for Large Spatial Datasets
- Scalable Gaussian Process Computations Using Hierarchical Matrices
- A Guide to Graph Colouring
- Handbook of Spatial Statistics
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- LAPACK Users' Guide
- A Full Scale Approximation of Covariance Functions for Large Spatial Data Sets
- Approximating Likelihoods for Large Spatial Data Sets
- Gaussian Markov Random Fields
- A class of multi-resolution approximations for large spatial datasets
- Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
- Hierarchical Spatial Process Models for Multiple Traits in Large Genetic Trials
- Cross-covariance functions for multivariate random fields based on latent dimensions
- Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets
- An updated set of basic linear algebra subprograms (BLAS)
- Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
- Graph colouring and the probabilistic method
- A general framework for Vecchia approximations of Gaussian processes