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A Class of Hartley-Ross-Type Estimators for Population Mean in Adaptive and Stratified Adaptive Cluster Sampling

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Abstract

In this article, we propose a class of Hartley-Ross-type unbiased estimators of finite population mean under adaptive cluster sampling and stratified adaptive cluster sampling. The estimators utilize information on known parameters of the auxiliary variable. The variances of proposed class of unbiased estimators are obtained up to first degree of approximation. Proposed estimators are more efficient than the usual mean estimator, ratio, and modified ratio estimators in adaptive cluster sampling and stratified adaptive cluster sampling under certain realistic conditions. Simulation study considering different populations is carried out to support the theoretical findings.

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References

  • Chao CT, Dryver AL, Chiang TZ (2011) Leveraging the Rao–Blackwell theorem to improve ratio estimators in adaptive cluster sampling. Environ Ecol Stat 18:543–568

    Article  MathSciNet  Google Scholar 

  • Christman MC, Lan F (2001) Inverse adaptive cluster sampling. Biometrics 57:1096–1105

    Article  MathSciNet  MATH  Google Scholar 

  • Chutiman N (2010) A new ratio estimator in stratified adaptive cluster sampling. Thail Stat 8:223–233

    MATH  Google Scholar 

  • Chutiman N (2013a) Adaptive cluster sampling using auxiliary variable. J Math Stat 9(3):249–255

    Article  Google Scholar 

  • Chutiman N, Chiangpradit M, Suraphee S (2013) A new estimator using auxiliary information in stratified adaptive cluster sampling. Open J Stat 3:278–282

    Article  MATH  Google Scholar 

  • Dryver AL, Chao CT (2007) Ratio estimators in adaptive cluster sampling. Environmetrics 18:607–620

    Article  MathSciNet  Google Scholar 

  • Dryver AL, Thompson SK (2005) Improved unbiased estimators in adaptive cluster sampling. J R Stat Soc 67:157–166

    Article  MathSciNet  MATH  Google Scholar 

  • Dryver AL, Nethran U, Smith DR (2012) Partial systematic adaptive cluster sampling. Environmetrics 23:306–316

    Article  MathSciNet  Google Scholar 

  • Félix-Medina MH, Thompson SK (2004) Adaptive cluster double sampling. Biometrica 91:877–891

    Article  MathSciNet  MATH  Google Scholar 

  • Gattone SA, Mohamed E, Dryver AL, Munnich RT (2016) Adaptive cluster sampling for negatively correlated data. Environmetrics 27:103–113

    Article  MathSciNet  Google Scholar 

  • Hartley HO, Ross A (1954) Unbiased ratio estimators. Nature 174:270–272

    Article  Google Scholar 

  • Lin F, Chao C (2014) Variances and variance estimators of the improved ratio estimators under adaptive cluster sampling. Environ Ecol Stat 21:285–311

    Article  MathSciNet  Google Scholar 

  • Muttlak HA, Khan A (2002) Adjusted two-stage adaptive cluster sampling. Environ Ecol Stat 9:111–120

    Article  MathSciNet  MATH  Google Scholar 

  • Singh HP, Sharma B, Tailor R (2014) Hartley–Ross type estimators for population mean using known parameters of auxiliary variate. Commun Stat Theory Methods 43:547–565

    Article  MathSciNet  MATH  Google Scholar 

  • Smith DR, Conroy MJ, Brakhage DH (1995) Efficiency of adaptive cluster sampling for estimating density of wintering waterfowl. Biometrics 51:777–788

    Article  Google Scholar 

  • Thompson SK (1990) Adaptive cluster sampling. J Am Stat Assoc 85:1050–1059

    Article  MathSciNet  MATH  Google Scholar 

  • Thompson SK (1991) Stratified adaptive cluster sampling. Biometrika 78:389–397

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors are thankful to the editor and anonymous referees for their valuable suggestions, which helped to improve the article.

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Authors and Affiliations

  1. Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan

    Faryal Younis & Javid Shabbir

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  1. Faryal Younis
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  2. Javid Shabbir
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Correspondence to Faryal Younis.

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Younis, F., Shabbir, J. A Class of Hartley-Ross-Type Estimators for Population Mean in Adaptive and Stratified Adaptive Cluster Sampling. Iran J Sci Technol Trans Sci 43, 1619–1627 (2019). https://doi.org/10.1007/s40995-018-0552-6

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  • DOI: https://doi.org/10.1007/s40995-018-0552-6

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