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New ratio and difference estimators of the finite population distribution function

Author

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  • Muñoz, J.F.
  • Arcos, A.
  • Álvarez, E.
  • Rueda, M.

Abstract

New design-based ratio and difference estimators of the distribution function are defined by minimizing the mean square error of a class of estimators. Proposed estimators do not assume a superpopulation model between the variable of interest and the auxiliary variable. Results derived from simulation studies indicate that proposed estimators can be more accurate than existing estimators, especially when alternative estimators suffer from model misspecifications.

Suggested Citation

  • Muñoz, J.F. & Arcos, A. & Álvarez, E. & Rueda, M., 2014. "New ratio and difference estimators of the finite population distribution function," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 102(C), pages 51-61.
  • Handle: RePEc:eee:matcom:v:102:y:2014:i:c:p:51-61
    DOI: 10.1016/j.matcom.2013.04.027
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    References listed on IDEAS

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    1. M. Rueda & J.F. Muñoz, 2009. "New Model‐assisted Estimators for the Distribution Function Using the Pseudo Empirical Likelihood Method," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 227-244, May.
    2. Rueda, M. M. & Arcos, A. & Martinez-Miranda, M. D. & Roman, Y., 2004. "Some improved estimators of finite population quantile using auxiliary information in sample surveys," Computational Statistics & Data Analysis, Elsevier, vol. 45(4), pages 825-848, May.
    3. P. M. Lerman, 1980. "Fitting Segmented Regression Models by Grid Search," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 77-84, March.
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    Cited by:

    1. Ayesha Khalid & Aamir Sanaullah & Mohammed M. A. Almazah & Fuad S. Al-Duais, 2023. "An Efficient Ratio-Cum-Exponential Estimator for Estimating the Population Distribution Function in the Existence of Non-Response Using an SRS Design," Mathematics, MDPI, vol. 11(6), pages 1-15, March.

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