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A generalised instrumental variable estimator for multivariable errors-in-variables identification problems

机译:用于多变量变量识别问题的广义工具变量估计器

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摘要

A new and very general estimation method, the generalised instrumental variable estimator (GIVE) has been introduced to deal with the errors-in-variables identification. The GIVE contains several well-known estimation methods as special cases that can be obtained by various user choices in GIVE. These methods include the bias-eliminating least squares method, a number of different versions of the Frisch scheme and the extended compensated least squares method. This article shows how previous analysis for single-input single-output systems can be extended in a non-trivial way to also cope with multi-input multi-output systems. Various computational aspects of GIVE are presented, and it is shown how the parameter estimates can be computed in an efficient way. The asymptotic distribution of the parameter estimates is also derived and analysed.
机译:引入了一种新的非常通用的估计方法,即广义工具变量估计器(GIVE),以处理变量误差识别。 GIVE包含几种众所周知的估计方法,这些特殊情况可以通过GIVE中的各种用户选择来获得。这些方法包括消除偏差的最小二乘法,Frisch方案的许多不同版本以及扩展的补偿最小二乘法。本文显示了如何以非平凡的方式扩展以前对单输入单输出系统的分析,以应对多输入多输出系统。介绍了GIVE的各种计算方面,并显示了如何以有效的方式计算参数估计。还推导并分析了参数估计的渐近分布。

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