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An improved estimation in stratified random sampling

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  • Ramkrishna S. Solanki
  • Housila P. Singh

Abstract

The article suggests a class of estimators of population mean in stratified random sampling using auxiliary information with its properties. In addition, various known estimators/classes of estimators are identified as members of the suggested class. It has been shown that the suggested class of estimators under optimum condition performs better than the usual unbiased, usual combined ratio, usual combined regression, Kadilar and Cingi (2005), Singh and Vishwakarma (2006) estimators and the members belonging to the classes of estimators envisaged by Kadilar and Cingi (2003), Singh, Tailor et al. (2008), Singh et al. (2009), Singh and Vishwakarma (2010) and Koyuncu and Kadilar (2010).

Suggested Citation

  • Ramkrishna S. Solanki & Housila P. Singh, 2016. "An improved estimation in stratified random sampling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(7), pages 2056-2070, April.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:7:p:2056-2070
    DOI: 10.1080/03610926.2013.826367
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    Cited by:

    1. Singh Housila P. & Mehta Vishal, 2017. "Improved Estimation of the Scale Parameter for Log-Logistic Distribution Using Balanced Ranked Set Sampling," Statistics in Transition New Series, Statistics Poland, vol. 18(1), pages 53-74, March.
    2. Shashi Bhushan & Anoop Kumar & Usman Shahzad & Amer Ibrahim Al-Omari & Ibrahim Mufrah Almanjahie, 2022. "On Some Improved Class of Estimators by Using Stratified Ranked Set Sampling," Mathematics, MDPI, vol. 10(18), pages 1-32, September.

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