Dependent Ranked Set Sampling Designs for Parametric Estimation with Applications

M. A. Sabry and M. Shaaban ()
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M. A. Sabry: Cairo University
M. Shaaban: The High Institute for Tourism, Hotels and Computer

Annals of Data Science, 2020, vol. 7, issue 2, No 9, 357-371

Abstract: Abstract In this paper, we derive the likelihood function of the neoteric ranked set sampling (NRSS) as dependent in sampling method and double neoteric ranked set sampling (DNRSS) designs as combine between independent sampling method in the first stage and dependent sampling method in the second stage and they compared for the estimation of the parameters of the inverse Weibull (IW) distribution. An intensive simulation has been made to compare the one and the two stages designs. The results showed that likelihood estimation based on ranked set sampling (RSS) as independent sampling method, NRSS and DNRSS designs provide more efficient estimators than the usual simple random sampling design. Moreover, the DNRSS is slightly more efficient than the NRSS and RSS designs in the case of estimating the IW distribution parameters.

Keywords: Simple random sampling; Ranked set sampling; Neoteric ranked set sampling; Double neoteric ranked set sampling; Maximum likelihood estimation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40745-020-00247-3

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