TLS and Its Improvements by Semiparametric Approach

Shun-ichi Amari () and Motoaki Kawanabe ()
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Shun-ichi Amari: RIKEN Brain Science Institute
Motoaki Kawanabe: Fraunhofer FIRST, The IDA group

A chapter in Total Least Squares and Errors-in-Variables Modeling, 2002, pp 15-24 from Springer

Abstract: Abstract The total least squares method seems to give a good consistent estimator in the linear error-in-variables model. However, this is not the optimal one. We give a simple adaptive method of improving the TLS estimator. The theory is based on information geometry of semiparametric statistical models, and is applicable to many other problems. Its intuitive introduction is also given.

Keywords: information geometry; semiparametric approach; linear errors-in-variables; estimating function; total least squares; structural relationship. (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-017-3552-0_2

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DOI: 10.1007/978-94-017-3552-0_2

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