Large-Scale Estimation of Variance and Covariance Components

1995 ◽  
Vol 16 (1) ◽  
pp. 192-209 ◽  
Author(s):  
Chris Fraley ◽  
Patrick J. Burns
Keyword(s):  
Large Scale ◽  
Scale Estimation ◽  
Covariance Components ◽  
Variance And Covariance Components ◽  
Estimation Of Variance

scholarly journals Mixed model approaches for diallel analysis based on a bio-model

1996 ◽  
Vol 68 (3) ◽  
pp. 233-240 ◽  
Author(s):  
Jun Zhu ◽  
Bruce S. Weir
Keyword(s):  
Mixed Model ◽  
Diallel Analysis ◽  
Worked Examples ◽  
Genetic Effects ◽  
Unbiased Estimation ◽  
Paternal Effects ◽  
Covariance Components ◽  
Variance And Covariance Components ◽  
Parameter Values ◽  
Estimation Of Variance

SummaryA MINQUE(l) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(l), restricted maximum likelihood (REML) and MINQUE(θ) which has parameter values for the prior values. MINQUE(l) is almost as efficient as MINQUE(θ) for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

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