More Efficient Approximation of Multiple Integrals using Steady State Ranked Simulated Sampling

DOI10.1080/03610918.2011.636856zbMath1266.65003OpenAlexW2080166428MaRDI QIDQ5299829

Hani M. Samawi, Robert L. Vogel

Publication date: 21 June 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.636856

zbMATH Keywords

importance samplingMonte Carlo methodsranked set samplingmultiple integrationbivariate ranked simulated samplingsteady state ranked simulated sampling

Mathematics Subject Classification ID

Order statistics; empirical distribution functions (62G30) Monte Carlo methods (65C05)

Related Items (3)

Steady-state Gibbs sampler estimation for lung cancer data ⋮ A more efficient Gibbs sampler estimation using steady-state simulation: applications to public health studies ⋮ Ranked simulated resampling: a more efficient and accurate resampling approximations for bootstrap inference

Cites Work

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• Controlled sampling using ranked set sampling
• More efficient monte carlo methods obtained by using ranked set simulated samples
• On the efficiency of monte carlo methods using steady state ranked simulated samples
• Monte Carlo strategies in scientific computing

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