Bayesian Nonparametric Variable Selection

Bayesian Nonparametric Variable Selection is a statistical framework that integrates Bayesian nonparametric methods with variable selection procedures, enabling flexible modeling of covariate inclusion probabilities without prespecifying the number of relevant predictors.

13

Publications

1.4K

Citations

37

Authors

26

Institutions

Publications per year

2017–2026

3

Authors

37

  1. BJ
    Brian J. Reich

    North Carolina State University, United States

    2 publications · 159 citations

    2

    h-index

  2. FV
    Francesco Versace

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 100 citations

    2

    h-index

  3. MV
    Marina Vannucci

    Rice University, United States

    2 publications · 100 citations

    2

    h-index

  4. MG
    Michele Guindani

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 100 citations

    2

    h-index

  5. FA
    Fernanda Araújo Pimentel Peres

    Universidade Federal do Rio Grande do Sul, Brazil

    1 publications · 128 citations

    1

    h-index

1–5 of 37

Venues

  1. Computers & Industrial Engineering

    1 publications · 128 citations

    1

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  2. Statistics in Medicine

    1 publications · 20 citations

    1

    h-index

  3. Bayesian Analysis

    1 publications · 25 citations

    1

    h-index

  4. International Journal of Medical Informatics

    1 publications · 277 citations

    1

    h-index

  5. The Annals of Applied Statistics

    AOAS · 1 publications · 47 citations

    1

    h-index

1–5