Efficient importance sampling for binary contingency tables
From MaRDI portal
Publication:2389598
DOI10.1214/08-AAP558zbMath1180.65010arXiv0908.0999OpenAlexW3099324675MaRDI QIDQ2389598
Publication date: 17 July 2009
Published in: The Annals of Applied Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0908.0999
importance samplingMarkov processesbipartite graphsapproximate countingDoob \(h\)-transformrare-event simulationbinary tableschanges-of-measure
Related Items
The Convergence Rate and Asymptotic Distribution of the Bootstrap Quantile Variance Estimator for Importance Sampling, Nonasymptotic performance analysis of importance sampling schemes for small noise diffusions, A sequential algorithm for generating random graphs, Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities, Negative examples for sequential importance sampling of binary contingency tables, Efficient Monte Carlo for high excursions of Gaussian random fields, Sampling for Conditional Inference on Network Data, Characterizing optimal sampling of binary contingency tables via the configuration model, Approximation of bounds on mixed-level orthogonal arrays, Counting subsets of contingency tables, Generating Random Networks Without Short Cycles, A Decomposition Based Proof for Fast Mixing of a Markov Chain over Balanced Realizations of a Joint Degree Matrix
Cites Work
- The complexity of computing the permanent
- Markov chains and stochastic stability
- Asymptotic enumeration of sparse 0--1 matrices with irregular row and column sums
- Efficient rare-event simulation for the maximum of heavy-tailed random walks
- Non-asymptotic bandwidth selection for density estimation of discrete data
- Introduction to rare event simulation.
- Negative examples for sequential importance sampling of binary contingency tables
- Stochastic simulation: Algorithms and analysis
- A Sequential Importance Sampling Algorithm for Generating Random Graphs with Prescribed Degrees
- Importance Sampling for Stochastic Simulations
- Conditional brownian motion and the boundary limits of harmonic functions
- State-dependent importance sampling for regularly varying random walks
- A Sequential Algorithm for Generating Random Graphs
- Weighted finite population sampling to maximize entropy
- Probability and Computing
- Sequential Monte Carlo Methods for Statistical Analysis of Tables
- Generating random regular graphs
- Sampling binary contingency tables with a greedy start
- Monte Carlo strategies in scientific computing
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
