On Time Series Analysis for Repeated Surveys (original) (raw)

Abstract

Governments and other agencies repeated many important surveys at regular time intervals, but the population mean is estimated mainly using the latest survey. Time series estimators for the population mean using repeated surveys are superior to those obtained from the last survey. This superiority may be affected by several factors such as the sampling variance, the number of surveys, and the Auto Regressive Moving Average ARMA model coefficients and orders among others. The main objective of the paper is to compare the time series estimator for repeated surveys developed by Scott et al. (A.J. Scott, T.M.F. Smith, R.G. Jones, Int. Stat. Rev. 45 (1977), 13–28.) and the last survey estimator using extensive simulation studies. Furthermore, the impact of the factors that may affect the efficiency of the time series estimator is also investigated.

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Authors and Affiliations

  1. Statistics Department, Cairo University, Egypt
    Mohamed A. Ismail (Professor)
  2. Statistics Department, Helwan University, Egypt
    Hend A. Auda (Associate Professor)
  3. National Centre for Statistics & Information, Egypt
    Yehia Ahmed Elzafrany (Statistical Advisor)

Authors

  1. Mohamed A. Ismail
  2. Hend A. Auda
  3. Yehia Ahmed Elzafrany

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Correspondence toMohamed A. Ismail.

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Ismail, M.A., Auda, H.A. & Elzafrany, Y.A. On Time Series Analysis for Repeated Surveys.J Stat Theory Appl 17, 587–596 (2018). https://doi.org/10.2991/jsta.2018.17.4.1

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2000 Mathematics Subject Classification