Monte Carlo Analysis

Monte Carlo Analysis is a computational technique that belongs to the class of numerical methods relying on repeated random sampling to approximate the probability distribution of an output variable, distinguished by its use of stochastic simulation to analyze the behavior and performance of systems under uncertainty.

4.6K

Publications

317.5K

Citations

16.5K

Authors

3.1K

Institutions

Publications per year

2017–2026

727

Authors

16.5K

  1. PW
    Peter W. Glynn

    Stanford University, United States

    16 publications · 1.6K citations

    14

    h-index

  2. EZ
    Enrico Zio

    Politecnico di Milano, Italy

    15 publications · 855 citations

    13

    h-index

  3. TG
    T. González

    Universidad de Salamanca, Spain

    13 publications · 303 citations

    12

    h-index

  4. RH
    Robert H. Swendsen

    Carnegie Mellon University, United States

    11 publications · 6.3K citations

    11

    h-index

  5. LF
    Luis F. Ochoa

    University of Manchester, United Kingdom

    11 publications · 842 citations

    11

    h-index

1–5 of 16.5K

Venues

  1. Journal of the American Statistical Association

    60 publications · 18K citations

    35

    h-index

  2. Physical Review Letters

    PRL · 39 publications · 9.6K citations

    32

    h-index

  3. IEEE Transactions on Power Systems

    35 publications · 3.2K citations

    31

    h-index

  4. Technometrics

    39 publications · 32.9K citations

    30

    h-index

  5. Computer Physics Communications

    47 publications · 4.4K citations

    28

    h-index

1–5