Multivariate Variance Components Analysis

Multivariate Variance Components Analysis is a statistical methodology that decomposes the covariance structure of multiple phenotypic traits into additive genetic, environmental, and other random effects components by jointly modeling their variances and covariances across related individuals.

61

Publications

3.6K

Citations

158

Authors

82

Institutions

Publications per year

2017–2026

7

Authors

158

  1. JA
    James A. Calvin

    Texas A&M University, United States

    4 publications · 106 citations

    4

    h-index

  2. RL
    Richard L. Dykstra

    University of Iowa, United States

    3 publications · 78 citations

    3

    h-index

  3. TW
    T. W. Anderson

    Stanford University, United States

    3 publications · 96 citations

    3

    h-index

  4. YA
    Yasuo Amemiya

    Iowa State University, United States

    2 publications · 30 citations

    2

    h-index

  5. RT
    R. Thompson

    Rothamsted Research, United Kingdom

    2 publications · 256 citations

    2

    h-index

1–5 of 158

Venues

  1. Journal of Multivariate Analysis

    6 publications · 159 citations

    6

    h-index

  2. Journal of the American Statistical Association

    4 publications · 1.5K citations

    4

    h-index

  3. The Annals of Statistics

    3 publications · 128 citations

    3

    h-index

  4. Genetic Epidemiology

    3 publications · 119 citations

    3

    h-index

  5. Biometrics

    3 publications · 132 citations

    3

    h-index

1–5