Product-form estimators: exploiting independence to scale up Monte Carlo

DOI10.1007/s11222-021-10069-9zbMath1477.62011arXiv2102.11575OpenAlexW3132189042MaRDI QIDQ2066757

Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen

Publication date: 14 January 2022

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2102.11575

zbMATH Keywords

importance samplingvariance reductionU-statisticslimit theoremsdimensionality reductionconditional independencepseudo-marginal methodsproduct-form distributions

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Monte Carlo methods (65C05)

Related Items (2)

The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems ⋮ A principled stopping rule for importance sampling

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The pseudo-marginal approach for efficient Monte Carlo computations
• Establishing some order amongst exact approximations of MCMCs
• Product-form stationary distributions for deficiency zero chemical reaction networks
• An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations
• Estimation of integrated squared density derivatives
• The jackknife estimate of variance
• Numerical integration using sparse grids
• Dimension-adaptive tensor-product quadrature
• Importance sampling: intrinsic dimension and computational cost
• Recycling physical random numbers
• Multivariate plug-in bandwidth selection
• Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms
• Ranking and empirical minimization of \(U\)-statistics
• Stochastic simulation: Algorithms and analysis
• Product-Form Poisson-Like Distributions and Complex Balanced Reaction Systems
• Unbiased Estimation with Square Root Convergence for SDE Models
• Empirical Processes with Applications to Statistics
• Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems
• Particle Filters for Partially Observed Diffusions
• Random-Weight Particle Filtering of Continuous Time Processes
• 10.1162/jmlr.2003.3.4-5.993
• Weighted Average Importance Sampling and Defensive Mixture Distributions
• An Introduction to Sequential Monte Carlo
• DESIGN BASED INCOMPLETE U-STATISTICS
• Variational Inference for Large-Scale Models of Discrete Choice
• Integration of Multimodal Functions by Monte Carlo Importance Sampling
• Networks of Waiting Lines
• A general method for debiasing a Monte Carlo estimator
• High-dimensional integration: The quasi-Monte Carlo way
• Modern Applied U‐Statistics
• Independent Particle Filters
• A Class of Statistics with Asymptotically Normal Distribution
• A Non-Parametric Test of Independence
• The Theory of Unbiased Estimation
• Large-sample asymptotics of the pseudo-marginal method
• Monte Carlo strategies in scientific computing
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

This page was built for publication: Product-form estimators: exploiting independence to scale up Monte Carlo