Density Estimation Under Censoring

Density Estimation Under Censoring is a statistical methodology that belongs to the class of density estimation techniques, distinguished by its adaptation to infer the underlying probability density function of a random variable when observations are subject to censoring, whereby only partial or incomplete data are available due to detection limits or truncation mechanisms.

130

Publications

5K

Citations

213

Authors

144

Institutions

Publications per year

2017–2026

18

Variants

Censored Density Estimation

Authors

213

  1. WJ
    W. J. Padgett

    University of South Carolina, United States

    5 publications · 223 citations

    5

    h-index

  2. HL
    Han‐Ying Liang

    Tongji University, China

    5 publications · 79 citations

    5

    h-index

  3. RC
    Ricardo Cao

    Universidade da Coruña, Spain

    5 publications · 78 citations

    5

    h-index

  4. FC
    Fabienne Comte

    Université Paris Cité, France

    5 publications · 124 citations

    5

    h-index

  5. CC
    Christophe Chesneau

    Université de Caen Normandie, France

    4 publications · 90 citations

    4

    h-index

1–5 of 213

Venues

  1. Journal of Multivariate Analysis

    11 publications · 362 citations

    11

    h-index

  2. The Annals of Statistics

    8 publications · 463 citations

    8

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 6 publications · 312 citations

    6

    h-index

  4. Journal of Statistical Planning and Inference

    6 publications · 156 citations

    6

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 4 publications · 150 citations

    4

    h-index

1–5