Sup-wald Test

The Sup-Wald Test is a statistical hypothesis test for detecting structural breaks in regression models, distinguished by its use of the supremum of a sequence of Wald statistics computed over all possible break points within a specified interval.

20

Publications

1.8K

Citations

31

Authors

31

Institutions

Publications per year

2017–2026

2

Variants

Supremum Wald Test

Authors

31

  1. PP
    Pierre Perrón

    Boston University, United States

    4 publications · 102 citations

    4

    h-index

  2. YW
    Yangru Wu

    Rutgers, The State University of New Jersey, United States

    3 publications · 1.2K citations

    3

    h-index

  3. PC
    Peter C.B. Phillips

    Yale University, United States

    3 publications · 1.2K citations

    3

    h-index

  4. JY
    Jun Yu

    Singapore Management University, Singapore

    3 publications · 1.2K citations

    3

    h-index

  5. MK
    Mohitosh Kejriwal

    Purdue University West Lafayette, United States

    2 publications · 72 citations

    2

    h-index

1–5 of 31

Venues

  1. SSRN Electronic Journal

    Repository · 4 publications · 85 citations

    4

    h-index

  2. Journal of Time Series Analysis

    3 publications · 81 citations

    3

    h-index

  3. Econometric Theory

    2 publications · 67 citations

    2

    h-index

  4. Econometric Reviews

    2 publications · 39 citations

    2

    h-index

  5. Journal of Business and Economic Statistics

    JBES · 2 publications · 33 citations

    2

    h-index

1–5