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Modified ratio estimators using robust regression methods

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  • Tolga Zaman
  • Hasan Bulut

Abstract

When there is an outlier in the data set, the efficiency of traditional methods decreases. In order to solve this problem, Kadilar et al. (2007) adapted Huber-M method which is only one of robust regression methods to ratio-type estimators and decreased the effect of outlier problem. In this study, new ratio-type estimators are proposed by considering Tukey-M, Hampel M, Huber MM, LTS, LMS and LAD robust methods based on the Kadilar et al. (2007). Theoretically, we obtain the mean square error (MSE) for these estimators. We compared with MSE values of proposed estimators and MSE values of estimators based on Huber-M and OLS methods. As a result of these comparisons, we observed that our proposed estimators give more efficient results than both Huber M approach which was proposed by Kadilar et al. (2007) and OLS approach. Also, under all conditions, all of the other proposed estimators except Lad method are more efficient than robust estimators proposed by Kadilar et al. (2007). And, these theoretical results are supported with the aid of a numerical example and simulation by basing on data that includes an outlier.

Suggested Citation

  • Tolga Zaman & Hasan Bulut, 2019. "Modified ratio estimators using robust regression methods," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(8), pages 2039-2048, April.
  • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:8:p:2039-2048
    DOI: 10.1080/03610926.2018.1441419
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    Cited by:

    1. Shashi Bhushan & Anoop Kumar & Amer Ibrahim Al-Omari & Ghadah A. Alomani, 2023. "Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators," Mathematics, MDPI, vol. 11(9), pages 1-14, April.
    2. Usman Shahzad & Ishfaq Ahmad & Amelia V. GarcĂ­a-Luengo & Tolga Zaman & Nadia H. Al-Noor & Anoop Kumar, 2023. "Estimation of Coefficient of Variation Using Calibrated Estimators in Double Stratified Random Sampling," Mathematics, MDPI, vol. 11(1), pages 1-17, January.

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