Fitting large-scale structured additive regression models using Krylov subspace methods
From MaRDI portal
Publication:1658522
DOI10.1016/j.csda.2016.07.006zbMath1466.62190OpenAlexW2475522231WikidataQ114671399 ScholiaQ114671399MaRDI QIDQ1658522
Publication date: 14 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.07.006
Markov chain Monte CarloKrylov subspace methodsLanczos algorithmimage analysisGaussian Markov random fieldstructured additive regression
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Fast Sampling of Gaussian Markov Random Fields
- Approximate Bayesian inference for large spatial datasets using predictive process models
- Iterative numerical methods for sampling from high dimensional Gaussian distributions
- Parameter estimation in high dimensional Gaussian distributions
- Chebyshev approximation of log-determinants of spatial weight matrices
- A numerical solution using an adaptively preconditioned Lanczos method for a class of linear systems related with the fractional Poisson equation
- A survey of Lanczos procedures for very large real 'symmetric' eigenvalue problems
- Inference from iterative simulation using multiple sequences
- Generalized structured additive regression based on Bayesian P-splines
- Preconditioned Krylov Subspace Methods for Sampling Multivariate Gaussian Distributions
- MCMC-Based Image Reconstruction with Uncertainty Quantification
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Analysis of the Gibbs Sampler for Hierarchical Inverse Problems
- Numerical Methods for Large Eigenvalue Problems
- A restarted Lanczos approximation to functions of a symmetric matrix
- Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging
- On Optimal Short Recurrences for Generating Orthogonal Krylov Subspace Bases
- First-order intrinsic autoregressions and the de Wijs process
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Conditional Prior Proposals in Dynamic Models
- On Block Updating in Markov Random Field Models for Disease Mapping
- Approximating Likelihoods for Large Spatial Data Sets
- Gaussian Markov Random Fields
- Bayesian Analysis of Agricultural Field Experiments
- Approximate Likelihood for Large Irregularly Spaced Spatial Data
- Computational Variants of the Lanczos Method for the Eigenproblem
- Multivariate statistical modelling based on generalized linear models.
This page was built for publication: Fitting large-scale structured additive regression models using Krylov subspace methods