Projection Pursuit

Projection Pursuit is a multivariate statistical technique that identifies low-dimensional projections of high-dimensional data by optimizing a criterion function to reveal structurally interesting patterns, such as non-Gaussian structures or clusters, that deviate from randomness or normality.

475

Publications

43.1K

Citations

1.1K

Authors

512

Institutions

Publications per year

2017–2026

115

Authors

1.1K

  1. DC
    Dianne Cook

    Iowa State University, United States

    13 publications · 1.1K citations

    12

    h-index

  2. XY
    Xiaojun Yao

    Lanzhou University, China

    8 publications · 204 citations

    9

    h-index

  3. AB
    Andreas Buja

    University of Pennsylvania, United States

    8 publications · 970 citations

    8

    h-index

  4. JH
    Jerome H. Friedman

    Stanford University, United States

    7 publications · 5.5K citations

    7

    h-index

  5. QF
    Qiang Fu

    Northeast Agricultural University, China

    7 publications · 259 citations

    7

    h-index

1–5 of 1.1K

Venues

  1. The Annals of Statistics

    17 publications · 4.7K citations

    16

    h-index

  2. Journal of the American Statistical Association

    16 publications · 5.7K citations

    15

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 15 publications · 1.1K citations

    13

    h-index

  4. IEEE Transactions on Neural Networks

    12 publications · 7K citations

    11

    h-index

  5. 10

    h-index

1–5