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Asymptotic properties for LS estimators in EV regression model with dependent errors

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Abstract

In this paper, we establish the strong consistency and asymptotic normality for the least square (LS) estimators in simple linear errors-in-variables (EV) regression models when the errors form a stationary α-mixing sequence of random variables. The quadratic-mean consistency is also considered.

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Authors and Affiliations

  1. Department of Applied Mathematics & Physics, Anhui University of Technology and Science, Wuhu, 241000, China

    Guo-Liang Fan & Hong-Xia Xu

  2. Department of Mathematics, Tongji University, Shanghai, 200092, China

    Han-Ying Liang

  3. School of Science, Hangzhou Normal University, Hangzhou, 310036, China

    Jiang-Feng Wang

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  1. Guo-Liang Fan
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  2. Han-Ying Liang
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  3. Jiang-Feng Wang
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  4. Hong-Xia Xu
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Correspondence to Guo-Liang Fan.

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Fan, GL., Liang, HY., Wang, JF. et al. Asymptotic properties for LS estimators in EV regression model with dependent errors. AStA Adv Stat Anal 94, 89–103 (2010). https://doi.org/10.1007/s10182-010-0124-3

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  • DOI: https://doi.org/10.1007/s10182-010-0124-3

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