Statistical Programming Languages

Statistical Programming Languages is a class of programming languages distinguished by their specialized design for implementing statistical computations, data analysis, and visualization, typically featuring built-in support for probability distributions, inferential statistics, and data modeling operations.

240

Publications

434.5K

Citations

557

Authors

265

Institutions

Publications per year

2017–2026

67

Authors

557

  1. JM
    John M. Chambers

    AT&T (United States), United States

    6 publications · 628 citations

    6

    h-index

  2. JF
    John Fox

    McMaster University, Canada

    4 publications · 1.7K citations

    4

    h-index

  3. VK
    Vikash K. Mansinghka

    Massachusetts Institute of Technology, United States

    3 publications · 177 citations

    3

    h-index

  4. FW
    Frank Wood

    University of Oxford, United Kingdom

    3 publications · 141 citations

    3

    h-index

  5. DT
    Duncan Temple Lang

    University of California, Davis, United States

    3 publications · 51 citations

    3

    h-index

1–5 of 557

Venues

  1. Technometrics

    14 publications · 2.1K citations

    13

    h-index

  2. The American Statistician

    12 publications · 1.1K citations

    12

    h-index

  3. Journal of Statistical Software

    JSS · 12 publications · 1.5K citations

    10

    h-index

  4. Bioinformatics

    9 publications · 4.5K citations

    9

    h-index

  5. Journal of the American Statistical Association

    7 publications · 5.4K citations

    7

    h-index

1–5