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arXiv 0710.0829math.NAcs.NAmath.STstat.TH
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计算线性最小二乘解分量的条件数

Computing the Conditioning of the Components of a Linear Least Squares Solution

CERFACS(法国计算与实验流体力学研究中心);University of Tennessee(田纳西大学);Oak Ridge National Laboratory(橡树岭国家实验室);University of Manchester(曼彻斯特大学);Centre National d’Etudes Spatiales(法国国家空间研究中心);University of Colorado at Denver and Health Sciences Center(科罗拉多大学丹佛分校健康科学中心)

Marc Baboulin, Jack Dongarra, Serge Gratton, Julien Langou

AI总结:

本文针对超定满秩线性最小二乘问题,基于Arioli等人的理论结果,定义了可计算的条件数估计,并将其解释为统计量,同时提供了使用LAPACK例程的计算代码和成本分析,最后给出了历史实例和空间工业实验。

摘要:

本文讨论了超定满秩线性最小二乘问题结果的准确性。我们回顾了Arioli、Baboulin和Gratton在SIMAX 29(2):413--433, 2007中关于最小二乘解及其分量的条件数的理论结果,其中矩阵扰动以Frobenius范数或谱范数度量。然后我们定义了这些条件数的可计算估计,并将其解释为统计量。特别地,我们证明在经典线性统计模型中,解的一个分量的方差与右端项方差的比值正是该解分量在考虑右端项扰动时的条件数。我们还提供了使用LAPACK例程计算方差-协方差矩阵和最小二乘条件数的片段代码,并给出了相应的计算成本。最后,我们给出了一个小的历史数值例子,该例子被Laplace在《概率分析理论》(1820年)中用于计算木星的质量,以及来自航天工业的真实物理数据实验。

英文摘要:

In this paper, we address the accuracy of the results for the overdetermined full rank linear least squares problem. We recall theoretical results obtained in Arioli, Baboulin and Gratton, SIMAX 29(2):413--433, 2007, on conditioning of the least squares solution and the components of the solution when the matrix perturbations are measured in Frobenius or spectral norms. Then we define computable estimates for these condition numbers and we interpret them in terms of statistical quantities. In particular, we show that, in the classical linear statistical model, the ratio of the variance of one component of the solution by the variance of the right-hand side is exactly the condition number of this solution component when perturbations on the right-hand side are considered. We also provide fragment codes using LAPACK routines to compute the variance-covariance matrix and the least squares conditioning and we give the corresponding computational cost. Finally we present a small historical numerical example that was used by Laplace in Theorie Analytique des Probabilites, 1820, for computing the mass of Jupiter and experiments from the space industry with real physical data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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