Monte Carlo Error Analysis

Monte Carlo Error Analysis is a methodological framework within computational statistics that quantifies the uncertainty and approximation error in Monte Carlo simulations by analyzing the variability of estimates derived from stochastic sampling processes.

379

Publications

47.3K

Citations

800

Authors

418

Institutions

Publications per year

2017–2026

57

Authors

800

  1. GL
    Galin L. Jones

    University of Minnesota, United States

    6 publications · 783 citations

    6

    h-index

  2. AB
    Art B. Owen

    Stanford University, United States

    6 publications · 860 citations

    6

    h-index

  3. BT
    Bruno Tuffin

    Institut national de recherche en sciences et technologies du numérique, France

    5 publications · 198 citations

    5

    h-index

  4. JM
    James M. Flegal

    University of California, Riverside, United States

    4 publications · 336 citations

    4

    h-index

  5. FY
    Frances Y. Kuo

    UNSW Sydney, Australia

    4 publications · 490 citations

    4

    h-index

1–5 of 800

Venues

  1. Nuclear Science and Engineering

    11 publications · 328 citations

    11

    h-index

  2. Annals of Nuclear Energy

    10 publications · 511 citations

    10

    h-index

  3. Computer Physics Communications

    11 publications · 616 citations

    10

    h-index

  4. SIAM Journal on Numerical Analysis

    9 publications · 855 citations

    9

    h-index

  5. arXiv (Cornell University)

    Repository · 8 publications · 237 citations

    8

    h-index

1–5