Efficient Simulation of High Dimensional Gaussian Vectors

DOI10.1287/moor.2017.0914OpenAlexW2950429661WikidataQ129289386 ScholiaQ129289386MaRDI QIDQ5219708

Nabil Kahale

Publication date: 12 March 2020

Published in: Mathematics of Operations Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.08738

zbMATH Keywords

Cholesky factorizationMonte Carlo simulationMarkov chainhigh dimensionGaussian vectors

Mathematics Subject Classification ID

Monte Carlo methods (65C05)

Uses Software

• ProbForecastGOP
• Krylstat

Cites Work

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• Fast Sampling of Gaussian Markov Random Fields
• A practical volume algorithm
• Model-based geostatistics.
• Iterative numerical methods for sampling from high dimensional Gaussian distributions
• The Frechet distance between multivariate normal distributions
• Hit-and-run mixes fast
• Statistical Distributions
• Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions
• The Markov chain Monte Carlo revolution
• A Chernoff Bound for Random Walks on Expander Graphs
• Improved Bounds for Mixing Rates of Markov Chains and Multicommodity Flow
• Large Deviation Bounds for Markov Chains
• Fast and Exact Simulation of Stationary Gaussian Processes through Circulant Embedding of the Covariance Matrix
• Learning to Optimize via Posterior Sampling
• Statistics for Spatial Data
• Hit-and-Run Algorithms for Generating Multivariate Distributions
• Calibrated Probabilistic Mesoscale Weather Field Forecasting
• Optimal Transport

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