Sequential Order Statistics

Sequential Order Statistics is a statistical model that extends the concept of order statistics by allowing each stage of an ordered sequence to depend recursively on the preceding stages, thereby capturing sequential dependencies in the distribution of ordered random variables.

104

Publications

5.5K

Citations

173

Authors

93

Institutions

Publications per year

2017–2026

7

Authors

173

  1. MB
    Marco Burkschat

    RWTH Aachen University, Germany

    11 publications · 292 citations

    11

    h-index

  2. UK
    Udo Kamps

    RWTH Aachen University, Germany

    9 publications · 585 citations

    9

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  3. JN
    Jorge Navarro

    Universidad de Murcia, Spain

    6 publications · 147 citations

    6

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  4. PK
    Pranab Kumar Sen

    University of North Carolina at Chapel Hill, United States

    5 publications · 145 citations

    5

    h-index

  5. NB
    N. Balakrishnan

    McMaster University, Canada

    4 publications · 120 citations

    4

    h-index

1–5 of 173

Venues

  1. 6

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  2. Journal of Statistical Planning and Inference

    5 publications · 189 citations

    5

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  3. Journal of Applied Probability

    JAP · 5 publications · 107 citations

    5

    h-index

  4. Biometrika

    4 publications · 82 citations

    4

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  5. 4

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1–5