Recursive Parameter Estimation

Recursive Parameter Estimation is a statistical inference method that iteratively updates the estimate of a parameter as new data become available, distinguishing itself by employing a recursive formulation in which the current posterior distribution serves as the prior for the subsequent update within a Bayesian framework.

372

Publications

19.6K

Citations

708

Authors

357

Institutions

Publications per year

2017–2026

31

Authors

708

  1. FD
    Feng Ding

    Jiangnan University, China

    15 publications · 1.1K citations

    13

    h-index

  2. LX
    Ling Xu

    Jiangnan University, China

    5 publications · 752 citations

    5

    h-index

  3. PC
    Peter C. Young

    Australian National University, Australia

    5 publications · 274 citations

    5

    h-index

  4. EJ
    E. J. Hannan

    Australian National University, Australia

    4 publications · 566 citations

    4

    h-index

  5. LL
    Lennart Ljung

    Linköping University, Sweden

    4 publications · 365 citations

    4

    h-index

1–5 of 708

Venues

  1. IEEE Transactions on Automatic Control

    16 publications · 674 citations

    14

    h-index

  2. Automatica

    12 publications · 527 citations

    12

    h-index

  3. IEEE Transactions on Signal Processing

    10 publications · 1.6K citations

    10

    h-index

  4. IEEE Transactions on Information Theory

    11 publications · 661 citations

    10

    h-index

  5. IFAC Proceedings Volumes

    9 publications · 211 citations

    9

    h-index

1–5