Adaptive refined descriptive sampling algorithm for dependent variables using Iman and Conover method in Monte Carlo simulation

DOI10.1080/03610926.2019.1709645OpenAlexW2998763064MaRDI QIDQ5078574

Siham Kebaili, Abdelouhab Aloui, Sofia Guebli, Megdouda Ourbih-Tari

Publication date: 23 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1709645

zbMATH Keywords

Monte Carlo simulationvariance reductionsampling methodsIman and Conover method

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• getRDS

Cites Work

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• A distribution-free approach to inducing rank correlation among input variables
• On Latin hypercube sampling
• A general purpose module using refined descriptive sampling for installation in simulation systems
• A comparison of methods for selecting values of simulation input variables
• Large-sample variance of simulation using refined descriptive sampling: Case of independent variables
• A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
• Simulating Controlled Variate and Rank Correlations Based on the Power Method Transformation
• Large Sample Properties of Simulations Using Latin Hypercube Sampling
• Latin hypercube sampling with dependence and applications in finance