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Pedigree Analysis for Quantitative Traits: Variance Components without Matrix Inversion
E. A. Thompson and R. G. Shaw
Vol. 46, No. 2 (Jun., 1990), pp. 399-413
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2531445
Page Count: 15
You can always find the topics here!Topics: Statistical variance, Eigenvalues, Breeding, Maximum likelihood estimation, Genetics, Animal models, Algorithms, Biometrics, Statistical estimation, Eigenvectors
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Recent developments in the animal breeding literature facilitate estimation of the variance components in quantitative genetic models. However, computation remains intensive, and many of the procedures are restricted to specialized designs and models, unsuited to data arising from studies of natural populations. We develop algorithms that allow maximum likelihood estimation of variance components for data on arbitrary pedigree structures. The proposed methods can be implemented on microcomputers, since no intensive matrix computations or manipulations are involved. Although parts of our procedures have been previously presented, we unify these into an overall scheme whose intuitive justification clarifies the approach. Two examples are analyzed: one of data on a natural population of Salvia lyrata and the other of simulated data on an extended pedigree.
Biometrics © 1990 International Biometric Society