You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Estimating the Precision of Estimates of Genetic Parameters Realized from Multiple-Trait Selection Experiments
F. C. Gunsett, K. N. Andriano and J. J. Rutledge
Vol. 38, No. 4 (Dec., 1982), pp. 981-989
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2529878
Page Count: 9
You can always find the topics here!Topics: Phenotypic traits, Genetic parameters, Genetics, Estimation methods, Least squares, Population estimates, Statistical discrepancies, Biometrics, Covariance, Estimators for the mean
Were these topics helpful?See somethings inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
The genetic change from multiple-trait selection experiments can be equated to the regression of genotype on phenotype. This gives rise to a method of obtaining estimates of additive genetic variances and covariances. The method requires the use of selection weights, derived by means of the index-in-retrospect, to provide invariant solutions. Solution variance estimates obtained from Monte Carlo simulation do not agree with variance estimates from ordinary least squares methods. This indicates that the errors are distributed with some structure V. A form of V is proposed which utilizes knowledge of the errors. Monte Carlo variance estimates from generalized least squares (GLS) methods agree closely with the average variance estimates from GLS when the proposed V is used. Use of an estimated V, derived after the initial estimation procedure, is shown to provide adequate information on the variance of the estimates.
Biometrics © 1982 International Biometric Society