Minimum Variance Estimation

Minimum Variance Estimation is an estimation method within state estimation that belongs to the class of optimal estimators and is distinguished by its property of minimizing the variance of the estimation error among all unbiased estimators.

1K

Publications

73.3K

Citations

2K

Authors

831

Institutions

Publications per year

2017–2026

107

Authors

2K

  1. SS
    Shuli Sun

    Heilongjiang University, China

    11 publications · 452 citations

    10

    h-index

  2. CR
    C. Radhakrishna Rao

    Pennsylvania State University, United States

    8 publications · 905 citations

    8

    h-index

  3. TB
    Taras Bodnar

    Stockholm University, Sweden

    7 publications · 267 citations

    7

    h-index

  4. BU
    B. U. Ö. Sonnerup

    Dartmouth College, United States

    7 publications · 693 citations

    7

    h-index

  5. CH
    Chien‐Shu Hsieh

    Ta Hwa University of Science and Technology, Taiwan

    6 publications · 300 citations

    6

    h-index

1–5 of 2K

Venues

  1. Journal of the American Statistical Association

    56 publications · 3.9K citations

    27

    h-index

  2. The Annals of Mathematical Statistics

    38 publications · 2.9K citations

    25

    h-index

  3. Technometrics

    34 publications · 1.8K citations

    22

    h-index

  4. IEEE Transactions on Signal Processing

    30 publications · 2.7K citations

    22

    h-index

  5. IEEE Transactions on Automatic Control

    28 publications · 2.8K citations

    21

    h-index

1–5