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A strongly consistent information criterion for linear model selection based on M-estimation
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  • Published: March 1999

A strongly consistent information criterion for linear model selection based on M-estimation

  • Y. Wu1 &
  • M. M. Zen2 

Probability Theory and Related Fields volume 113, pages 599–625 (1999)Cite this article

  • 229 Accesses

  • 16 Citations

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Abstract

In this paper, a linear model selection procedure based on M-estimation is proposed, which includes many classical model selection criteria as its special cases. It is shown that the proposed criterion is strongly consistent under certain mild conditions, for instance without assuming normality of the distribution of the random errors. The results from a simulation study are also presented.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3. e-mail: wuyh@mathstat.yorku.ca, , , , , , CA

    Y. Wu

  2. Department of Statistics, National Cheng-Kung University, Tainan, Taiwan, , , , , , TW

    M. M. Zen

Authors
  1. Y. Wu
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  2. M. M. Zen
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Additional information

Received: 13 October 1997 / Revised version: 10 August 1998

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Cite this article

Wu, Y., Zen, M. A strongly consistent information criterion for linear model selection based on M-estimation. Probab Theory Relat Fields 113, 599–625 (1999). https://doi.org/10.1007/s004400050219

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  • Issue Date: March 1999

  • DOI: https://doi.org/10.1007/s004400050219

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  • Mathematics Subject Classification (1991): 62J05, 62F35, 62F12
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