Antithetic Variates

Antithetic Variates is a variance reduction technique in Monte Carlo simulation that belongs to the class of sampling methods by introducing negatively correlated (antithetic) pairs of random variables to reduce estimator variance through systematic balancing of sample paths.

77

Publications

4.8K

Citations

105

Authors

78

Institutions

Publications per year

2017–2026

4

Authors

105

  1. JR
    James R. Wilson

    North Carolina State University, United States

    6 publications · 289 citations

    6

    h-index

  2. WM
    W. M. Mikhail

    Cairo University, Egypt

    3 publications · 104 citations

    3

    h-index

  3. FM
    Farshid Mehrdoust

    University of Guilan, Iran

    3 publications · 51 citations

    3

    h-index

  4. GS
    George S. Fishman

    University of North Carolina at Chapel Hill, United States

    3 publications · 88 citations

    3

    h-index

  5. JM
    J. M. Hammersley

    University of Oxford, United Kingdom

    3 publications · 347 citations

    3

    h-index

1–5 of 105

Venues

  1. Operations Research

    6 publications · 295 citations

    6

    h-index

  2. Management Science

    4 publications · 128 citations

    4

    h-index

  3. 4

    h-index

  4. 3

    h-index

  5. Journal of Statistical Computation and Simulation

    JSCS · 3 publications · 54 citations

    3

    h-index

1–5