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Estimators for a Poisson parameter using ranked set sampling

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  • Vic Barnett
  • Maria Cecilia Mendes Barreto

Abstract

Using ranked set sampling, a viable BLUE estimator is obtained for estimating the mean of a Poisson distribution. Its properties, such as efficiency relative to the ranked set sample mean and to the maximum likelihood estimator, have been calculated for different sample sizes and values of the Poisson parameter. The estimator (termed the normal modified r.s.s. estimator is more efficient than both the ranked set sample mean and the MLE. It is recommended as a reasonable estimator of the Poisson mean ( u ) to be used in a ranked set sampling environment.

Suggested Citation

  • Vic Barnett & Maria Cecilia Mendes Barreto, 2001. "Estimators for a Poisson parameter using ranked set sampling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(8), pages 929-941.
    • Handle: RePEc:taf:japsta:v:28:y:2001:i:8:p:929-941
    DOI: 10.1080/02664760120076616
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    References listed on IDEAS

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    1. Sinha Bimal K. & Sinha Bikas K. & Purkayastha Sumitra, 1996. "On Some Aspects Of Ranked Set Sampling For Estimation Of Normal And Exponential Parameters," Statistics & Risk Modeling, De Gruyter, vol. 14(3), pages 223-240, March.
    2. Lynne Stokes, 1995. "Parametric ranked set sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 47(3), pages 465-482, September.
    3. Vic Barnett & Karen Moore, 1997. "Best linear unbiased estimates in ranked-set sampling with particular reference to imperfect ordering," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(6), pages 697-710.
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    Cited by:

    1. Zamanzade, Ehsan & Wang, Xinlei, 2017. "Estimation of population proportion for judgment post-stratification," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 257-269.

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