Level-3 Large Deviations

Level-3 Large Deviations is a theoretical framework within the theory of large deviations that characterizes the asymptotic behavior of empirical process measures on the space of probability measures, distinguishing itself by its focus on the large deviation principles for trajectories of stochastic processes at the level of occupation measures.

27

Publications

1.6K

Citations

68

Authors

43

Institutions

Publications per year

2017–2026

2

Variants

Level-3 Large Deviation PrincipleLevel-3 Ldp

Authors

68

  1. JZ
    Jianliang Zhai

    University of Science and Technology of China, China

    2 publications · 65 citations

    2

    h-index

  2. ER
    Eric R. Ziegel

    Kyocera (United States), United States

    2 publications · 163 citations

    2

    h-index

  3. KC
    Kam Chuen Yuen

    University of Hong Kong, Hong Kong SAR China

    2 publications · 91 citations

    2

    h-index

  4. TZ
    Tusheng Zhang

    University of Manchester, United Kingdom

    2 publications · 118 citations

    2

    h-index

  5. YC
    Yiqing Chen

    University of Hong Kong, Hong Kong SAR China

    2 publications · 91 citations

    2

    h-index

1–5 of 68

Venues

  1. Technometrics

    3 publications · 207 citations

    3

    h-index

  2. 2

    h-index

  3. Statistics & Probability Letters

    2 publications · 43 citations

    2

    h-index

  4. Applied Mathematics & Optimization

    2 publications · 118 citations

    2

    h-index

  5. Journal of Statistical Physics

    2 publications · 124 citations

    2

    h-index

1–5