TAILIEUCHUNG - Báo cáo sinh học: " A reparameterization to improve numerical optimization in multivariate REML (co)variance component estimation"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: A reparameterization to improve numerical optimization in multivariate REML (co)variance component estimation | Genet Sei Evol 1994 26 537-545 Elsevier INRA 537 Original article A reparameterization to improve numerical optimization in multivariate REML co variance component estimation E Groeneveld Institute of Animal Husbandry and Animal Behaviour Federal Agricultural Research Center Holtystr 10 31535 Neustadt Germany Received 28 February 1994 accepted 15 June 1994 Summary Multivariate restricted maximum likelihood REML co variance component estimation using numerical optimization on the basis of Downhill-Simplex DS or quasiNewton QN procedures suffers from the problem of undefined covariance matrices as are produced by the optimizers. So far this problem has been dealt with by assigning bad function values. For this procedure to work it is implied that the information this bad function value conveys is sufficient to avoid going in the same direction in the following optimization step. To a limited degree DS can cope with this situation. On the other hand QN usually breaks down if this situation occurs too frequently. This contribution analyzes the problem and proposes a reparameterization of the covariance matrices to solve it. As a result faster converging QN optimizers can be used as they no longer suffer from lack of robustness. Four real data sets were analyzed using a multivariate model estimating between 17 and 30 co variance components simultaneously. Optimizing on the Cholesky factor instead of on the co variance components themselves reduced the computing time by a factor of to more than 250 when comparing the robust modified DS optimizer operating on the original covariance matrices to a QN optimizer using reparameterized covariance matrices. multivariate REML optimization quasi-Newton Downhill Simplex reparameterization Resume Un reparamétrage pour améliorer 1 optimisation numérique dans une estimation REML multivariate de composantes de variance-covariance. L estimation du maximum de vraisemblance restreinte REML des composantes de variance-covariance à I .

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