A sampling method for estimating the accuracy of
predicted breeding values in genetic evaluation

Fouilloux, Marie-Noëlle; Laloë, Dénis

doi:10.1051/gse:2001128

Cited by 2 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Calculating variance components using more complete data sets would facilitate a reduction in the bias of estimated variance components caused by the ignoring of data on which selection has taken place in the population [12], due to computational limitations. Calculation of unbiased accuracy of within breed [8] and across breed [12] estimated breeding values can be improved by reducing the computational time required of calculation or reducing the sampling error for a given computational time. Application of an algorithm controlling the variance of response to selection [24] to large data sets can be speeded up.…”

Section: Discussionmentioning

confidence: 99%

“…The Monte Carlo sampling procedure for calculating the sampled PEV has been described extensively elsewhere for single breed [8-10] and multiple breed scenarios [12]. Assuming a simple additive genetic animal model without genetic groups y = Xb + Zu + e , where the distribution of random variables is y ~ N ( Xb , ZGZ ' + R ), u ~ N ( 0 , G ), and e ~ N ( 0 , R ), the three steps involved in calculating the sampled PEV are as follows: 1.…”

Section: Methodsmentioning

confidence: 99%

“…The first three formulations (PEV GC1 , PEV GC2 , and PEV GC3 ) were outlined by Garcia-Cortes et al [10] and the fourth formulation (PEV FL ) was outlined by Fouilloux and Laloë [8]. PEV AF1 , PEV AF2 , PEV AF3 , and PEV AF4 are alternative versions of these formulations, which rescale the formulations from the Var (u) and to the

σ_{g}^{2}

in order to account for the effects of sampling on the Var(u).…”

Section: Methodsmentioning

confidence: 99%

“…However different formulations have been presented to approximate the PEV in this way [8-11]. Approximations of the PEV using these formulations converge to the exact PEV ( PEV exact ) as the number of Monte Carlo samples increases, but the number of samples is generally limited by computational requirements in practice [ e.g.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

Hickey

Veerkamp²,

Calus³

et al. 2009

Genet Sel Evol

View full text Add to dashboard Cite

Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

σ_{g}^{2}

in order to account for the effects of sampling on the Var(u).…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

Hickey

Veerkamp²,

Calus³

et al. 2009

Genet Sel Evol

View full text Add to dashboard Cite

show abstract

Approximating prediction error covariances among additive genetic effects within animals in multiple‐trait and random regression models

Tier

Meyer

2004

J Animal Breeding Genetics

View full text Add to dashboard Cite

A method for approximating prediction error variances and covariances among estimates of individual animalsÕ genetic effects for multiple-trait and random regression models is described. These approximations are used to calculate the prediction error variances of linear functions of the terms in the model. In the multiple-trait case these are indexes of estimated breeding values, and for random regression models these are estimated breeding values at individual points on the longitudinal scale. Approximate reliabilities for terms in the model and linear functions thereof are compared with corresponding reliabilities obtained from the inverse of the coefficient matrix in the mixed model equations. Results show good agreement between approximate and ÔtrueÕ values. ZusammenfassungApproximative Scha¨tzung der Standardfehler der Kovarianzen zwischen additiv genetischen Tiereffekten in Mehrmerkmals-und zufa¨lligen RegressionsmodellenBeschrieben wird eine Methode zur approximativen Schätzung der Standardfehler der Varianzen und Kovarianzen zwischen Schätzwerten fü r tierindividuelle genetische Effekte fü r Mehrmerkmals-und zufällige Regressionsmodelle. Diese approximative Methode wird benutzt, um die Restvarianz von linearen Funktionen der Effekte im Modell zu schätzen. Im Falle von Mehrmerkmalsmodellen sind dies Indices der geschätzten Zuchtwerte, und fü r zufällige Regressionsmodelle sind dies geschätzte Zuchtwerte an individuellen Punkten der Funktion. Die approximativen Sicherheiten der Effekte im Modell und linearen Funktionen dieser werden mit den Sicherheiten aus der Inversen der Koeffizientenmatrix im Gleichungssystem des gemischten Modells verglichen. Die Ergebnisse zeigen eine gute Ü bereinstimung zwischen den approximativen und den ÔwahrenÕ Werten.

show abstract

A sampling method for estimating the accuracy of predicted breeding values in genetic evaluation

Cited by 2 publications

References 14 publications

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

Approximating prediction error covariances among additive genetic effects within animals in multiple‐trait and random regression models

Contact Info

Product

Resources

About