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A new method for the estimation of variance components directly from the sample covariance matrix

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  • Hisham El‐Shishiny
  • Hussein Mansour

Abstract

Statistical techniques for the estimation of variance components are usually associated with methodological and computational difficulties. In this paper a new computational method for the estimation of variance components directly from the sample covariance matrix is proposed. A comparison between this method and the maximum likelihood method for variance component estimation, based on their computational performance, is made. Cases for balanced and unbalanced simulated data assuming a two‐way nixed model with correlated errors are considered, and a real‐life application in animal breeding is presented.

Suggested Citation

  • Hisham El‐Shishiny & Hussein Mansour, 1988. "A new method for the estimation of variance components directly from the sample covariance matrix," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 4(4), pages 231-238, December.
    • Handle: RePEc:wly:apsmda:v:4:y:1988:i:4:p:231-238
    DOI: 10.1002/asm.3150040403
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