回顾了在嵌套误差模型下估计方差分量的REBLUP方法

Betsabé Pérez Pérez Garrido, Szabolcs Szilárd Sebrek
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引用次数: 0

摘要

本文旨在分析Sinha-Rao[2009]提出的REBLUP(稳健经验最佳线性无偏预测)方法,该方法用于计算嵌套误差单元级模型下方差分量的稳健估计量。它解释了与REBLUP方法相关的理论和计算方面,以揭示所提出方法的优点和缺点。然后进行蒙特卡罗研究,分析该方法在不同场景下的性能。
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Review of the REBLUP method for estimating variance components under the nested error model
E-mail: sebrek@uni-corvinus.hu The present work aims to analyse the REBLUP (robust empirical best linear unbiased prediction) method as proposed by Sinha–Rao [2009] for computing robust estimators of variance components under the nested error unit-level model. It explains the theoretical and computational aspects associated with the REBLUP method to reveal the strengths and weaknesses of the proposed approach. A Monte Carlo study is then conducted to analyse the method’s performance under different scenarios.
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