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The second-order derivatives of matrices of eigenvalues and eigenvectors with an application to generalized F-statistic

机译:特征值和特征向量矩阵的二阶导数及其在广义F统计中的应用

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In this paper we derive the second-order derivatives of an orthogonal matrix of eigenvectors and of a matrix of eigenvalues of a real symmetric matrix. Obtained expressions depend on the first-order derivatives of these matrices, which were presented in Linear Algebra Appl. 264 (1997) 489. These results we use to find the main term of the bias of a generalized F-statistic [Biometrical J. 38 (1996) 5] in the case of normal population. A simulation experiment is carried out, in which we compare the sample mean and unbiased estimator of F-statistic with its asymptotic mean, which was obtained in Linear Algebra Appl. 321 (2000) 27. (C) 2003 Elsevier Inc. All rights reserved.
机译:在本文中,我们推导了特征向量正交矩阵和实对称矩阵特征值矩阵的二阶导数。获得的表达式取决于这些矩阵的一阶导数,这些表达式在线性代数应用程序1中进行了介绍。 264(1997)489.在正常人群的情况下,我们使用这些结果来寻找广义F统计量的偏差的主要术语[Biometrical J. 38(1996)5]。进行了一个模拟实验,在该实验中,我们比较了在线性代数应用程序中获得的F统计量的样本均值和无偏估计量及其渐近均值。 321(2000)27.(C)2003 Elsevier Inc.保留所有权利。

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