Conditionally Poisson Sampling

Conditionally Poisson Sampling is a spatial sampling method that belongs to the class of probabilistic sampling designs in which the selection of sampling units follows a Poisson process conditioned on prespecified constraints or auxiliary information, distinguishing it by incorporating conditional probabilities to ensure adherence to desired spatial patterns or inclusion criteria.

15

Publications

664

Citations

31

Authors

34

Institutions

Publications per year

2017–2026

0

Authors

31

  1. JH
    J. H. Ahrens

    Christian-Albrechts-Universität zu Kiel, Germany

    2 publications · 395 citations

    2

    h-index

  2. UD
    U. Dieter

    Graz University of Technology, Austria

    2 publications · 395 citations

    2

    h-index

  3. YB
    Yves Brunet

    Institut National de la Recherche Agronomique, Morocco

    1 publications · 14 citations

    1

    h-index

  4. RS
    Rolf Sundberg

    Stockholm University, Sweden

    1 publications · 11 citations

    1

    h-index

  5. VS
    V. Soundararajan

    Bharathiar University, India

    1 publications · 14 citations

    1

    h-index

1–5 of 31

Venues

  1. Journal of Statistical Planning and Inference

    3 publications · 73 citations

    3

    h-index

  2. Computing

    3 publications · 416 citations

    3

    h-index

  3. Scandinavian Journal of Statistics

    2 publications · 92 citations

    2

    h-index

  4. 1

    h-index

  5. Journal of Quality Technology

    1 publications · 14 citations

    1

    h-index

1–5