Parametric Bootstrap Testing

Parametric Bootstrap Testing is a statistical inference method that generates synthetic datasets under a specified parametric model to evaluate the goodness-of-fit of categorical models by comparing observed test statistics to their empirical distribution under the null hypothesis.

368

Publications

23.4K

Citations

789

Authors

454

Institutions

Publications per year

2017–2026

62

Authors

789

  1. WG
    Wenceslao González–Manteiga

    Universidade de Santiago de Compostela, Spain

    6 publications · 479 citations

    6

    h-index

  2. KK
    K. Krishnamoorthy

    University of Louisiana at Lafayette, United States

    5 publications · 274 citations

    5

    h-index

  3. KT
    Keith T. Poole

    University of Georgia, United States

    4 publications · 233 citations

    4

    h-index

  4. NP
    Nabendu Pal

    University of Louisiana at Lafayette, United States

    4 publications · 98 citations

    4

    h-index

  5. EM
    Enno Mammen

    Heidelberg University, Germany

    4 publications · 269 citations

    4

    h-index

1–5 of 789

Venues

  1. 14

    h-index

  2. 14

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  3. Biometrics

    11 publications · 605 citations

    11

    h-index

  4. Communication in Statistics- Theory and Methods

    12 publications · 263 citations

    11

    h-index

  5. SSRN Electronic Journal

    Repository · 10 publications · 287 citations

    10

    h-index

1–5