Conditional Monte Carlo

Conditional Monte Carlo is a variance reduction technique in computational statistics that belongs to the class of Monte Carlo methods, distinguished by its use of conditional expectations to reduce the variability of estimators through analytical integration over a subset of random variables.

56

Publications

2.2K

Citations

106

Authors

60

Institutions

Publications per year

2017–2026

12

Variants

Conditional Monte Carlo MethodConditional Monte Carlo Methods

Authors

106

  1. PL
    Pierre L’Ecuyer

    Université de Montréal, Canada

    4 publications · 155 citations

    4

    h-index

  2. HC
    Huub C. J. Hoefsloot

    University of Amsterdam, Netherlands

    4 publications · 85 citations

    4

    h-index

  3. PD
    Piet D. Iedema

    University of Amsterdam, Netherlands

    4 publications · 85 citations

    4

    h-index

  4. SA
    Søren Asmussen

    Aarhus University, Denmark

    4 publications · 327 citations

    4

    h-index

  5. DP
    Dirk P. Kroese

    The University of Queensland, Australia

    3 publications · 229 citations

    3

    h-index

1–5 of 106

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 63 citations

    4

    h-index

  2. Advances in Applied Probability

    AAP · 3 publications · 199 citations

    3

    h-index

  3. Management Science

    3 publications · 278 citations

    3

    h-index

  4. Polymer

    2 publications · 31 citations

    2

    h-index

  5. ACM Transactions on Modeling and Computer Simulation

    TOMACS · 2 publications · 29 citations

    2

    h-index

1–5