Markov Copula Models

Markov Copula Models is a statistical modeling framework that belongs to the class of copula-based dependence models, distinguished by its incorporation of Markovian dynamics to capture temporal dependence through a sequence of copulas conditional on past states.

35

Publications

1.6K

Citations

71

Authors

67

Institutions

Publications per year

2017–2026

12

Authors

71

  1. TR
    Tomasz R. Bielecki

    Illinois Institute of Technology, United States

    6 publications · 242 citations

    6

    h-index

  2. SC
    Stéphane Crépey

    Université d'Évry Val-d'Essonne, France

    5 publications · 214 citations

    5

    h-index

  3. AH
    Alexander Herbertsson

    University of Gothenburg, Sweden

    3 publications · 109 citations

    3

    h-index

  4. TE
    Takeshi Emura

    National Central University, Taiwan

    3 publications · 70 citations

    3

    h-index

  5. AC
    Areski Cousin

    Université Claude Bernard Lyon 1, France

    3 publications · 109 citations

    3

    h-index

1–5 of 71

Venues

  1. 3

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  2. SSRN Electronic Journal

    Repository · 3 publications · 50 citations

    3

    h-index

  3. Energy

    2 publications · 124 citations

    2

    h-index

  4. 2

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  5. Journal of Statistical Planning and Inference

    2 publications · 43 citations

    2

    h-index

1–5