Self-correcting Processes

Self-Correcting Processes is a feedback-driven counting process that dynamically adjusts its own parameters or trajectory in response to accumulated deviations, ensuring convergence toward a target count or state through internal error correction.

111

Publications

7.3K

Citations

286

Authors

167

Institutions

Publications per year

2017–2026

30

Authors

286

  1. SV
    Simine Vazire

    Washington University in St. Louis, United States

    4 publications · 195 citations

    4

    h-index

  2. TY
    Tal Yarkoni

    The University of Texas at Austin, United States

    2 publications · 108 citations

    2

    h-index

  3. RC
    Rickard Carlsson

    Linnaeus University, Sweden

    2 publications · 108 citations

    2

    h-index

  4. JP
    John P. A. Ioannidis

    Stanford University, United States

    2 publications · 1.1K citations

    2

    h-index

  5. SF
    Stacey F. Bent

    Stanford University, United States

    2 publications · 340 citations

    2

    h-index

1–5 of 286

Venues

  1. Perspectives on Psychological Science

    PPSC · 3 publications · 710 citations

    3

    h-index

  2. RePEc: Research Papers in Economics

    Repository · 3 publications · 54 citations

    3

    h-index

  3. Stochastic Processes and their Applications

    2 publications · 227 citations

    2

    h-index

  4. Journal of Consulting and Clinical Psychology

    2 publications · 221 citations

    2

    h-index

  5. Clinical Psychology Science and Practice

    2 publications · 170 citations

    2

    h-index

1–5