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Robust inference strategy in the presence of measurement error

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  • Ahmed, S. Ejaz
  • Hussein, Abdulkadir
  • Nkurunziza, Sévérien

Abstract

In this paper, we consider a statistical model where samples are subject to measurement errors. Further, we propose a shrinkage estimation strategy by using the maximum empirical likelihood estimator (MELE) as the base estimator. Our asymptotic results clearly demonstrate the superiority of our proposed shrinkage strategy over the MELE. Monte Carlo simulation results show that such a performance still holds in finite samples. We apply our method to real data set.

Suggested Citation

  • Ahmed, S. Ejaz & Hussein, Abdulkadir & Nkurunziza, Sévérien, 2010. "Robust inference strategy in the presence of measurement error," Statistics & Probability Letters, Elsevier, vol. 80(7-8), pages 726-732, April.
    • Handle: RePEc:eee:stapro:v:80:y:2010:i:7-8:p:726-732
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    References listed on IDEAS

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    1. Ahmed, S. Ejaz & Volodin, Andrei I. & Volodin, Igor N., 2009. "High order approximation for the coverage probability by a confident set centered at the positive-part James-Stein estimator," Statistics & Probability Letters, Elsevier, vol. 79(17), pages 1823-1828, September.
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    Cited by:

    1. Nkurunziza, Sévérien, 2011. "Shrinkage strategy in stratified random sample subject to measurement error," Statistics & Probability Letters, Elsevier, vol. 81(2), pages 317-325, February.
    2. Arashi, M. & Kibria, B.M. Golam & Norouzirad, M. & Nadarajah, S., 2014. "Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 53-74.
    3. Raheem, S.M. Enayetur & Ahmed, S. Ejaz & Doksum, Kjell A., 2012. "Absolute penalty and shrinkage estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 874-891.

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    3. Nkurunziza, Sévérien, 2011. "Shrinkage strategy in stratified random sample subject to measurement error," Statistics & Probability Letters, Elsevier, vol. 81(2), pages 317-325, February.

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