Sampling Schemes

Sampling Schemes is a methodological framework in high-frequency time series analysis that specifies the rules and intervals governing the selection of discrete observations from a continuous-time stochastic process to balance statistical efficiency and computational feasibility.

1.1K

Publications

62.2K

Citations

2.2K

Authors

943

Institutions

Publications per year

2017–2026

185

Authors

2.2K

  1. CB
    Carlo Bardaro

    University of Perugia, Italy

    10 publications · 391 citations

    10

    h-index

  2. PL
    P. L. Butzer

    RWTH Aachen University, Germany

    9 publications · 811 citations

    9

    h-index

  3. EM
    E. Masry

    University of California San Diego, United States

    9 publications · 472 citations

    9

    h-index

  4. MM
    Marek Miśkowicz

    AGH University of Krakow, Poland

    9 publications · 704 citations

    9

    h-index

  5. IM
    Ilaria Mantellını

    University of Perugia, Italy

    8 publications · 144 citations

    8

    h-index

1–5 of 2.2K

Venues

  1. IEEE Transactions on Signal Processing

    45 publications · 2.3K citations

    24

    h-index

  2. IEEE Transactions on Information Theory

    25 publications · 1.2K citations

    17

    h-index

  3. Journal of the American Statistical Association

    20 publications · 2.1K citations

    16

    h-index

  4. Technometrics

    17 publications · 683 citations

    14

    h-index

  5. Signal Processing

    18 publications · 373 citations

    14

    h-index

1–5