Iterative numerical methods for sampling from high dimensional Gaussian distributions
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Publication:892432
DOI10.1007/s11222-012-9326-8zbMath1325.65020OpenAlexW2015539995MaRDI QIDQ892432
Jo Eidsvik, Erlend Aune, Yvo Pokern
Publication date: 19 November 2015
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11222-012-9326-8
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Cites Work
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- Fast Sampling of Gaussian Markov Random Fields
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Parameter estimation in high dimensional Gaussian distributions
- A numerical solution using an adaptively preconditioned Lanczos method for a class of linear systems related with the fractional Poisson equation
- Analysis of the symmetric Lanczos algorithm with reorthogonalization methods
- Bayesian image restoration, with two applications in spatial statistics (with discussion)
- A Krylov subspace method for covariance approximation and simulation of random processes and fields
- Approximate inverse preconditioning for shifted linear systems
- Accurate conjugate gradient methods for families of shifted systems
- Numerical approximation of the product of the square root of a matrix with a vector
- Sampling Gaussian Distributions in Krylov Spaces with Conjugate Gradients
- A restarted Lanczos approximation to functions of a symmetric matrix
- Solving Systems of Linear Equations With a Positive Definite, Symmetric, but Possibly Ill-Conditioned Matrix
- The Lanczos and conjugate gradient algorithms in finite precision arithmetic
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Computing $A^\alpha, \log(A)$, and Related Matrix Functions by Contour Integrals
- Optimal and Superoptimal Circulant Preconditioners
- Fitting Gaussian Markov Random Fields to Gaussian Fields
- A Deflated Version of the Conjugate Gradient Algorithm
- Gaussian Markov Random Fields
- Functions of Matrices
- Methods of conjugate gradients for solving linear systems
