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- W2758358416 abstract "In this paper, we propose and evaluate the performance of different parametric and nonparametric estimators for the population coefficient of variation considering Ranked Set Sampling (RSS) under normal distribution. The performance of the proposed estimators was assessed based on the bias and relative efficiency provided by a Monte Carlo simulation study. An application in anthropometric measurements data from a human population is also presented. The results showed that the proposed estimators via RSS present an expressively lower mean squared error when compared to the usual estimator, obtained via Simple Random Sampling. Also, it was verified the superiority of the maximum likelihood estimator, given the necessary assumptions of normality and perfect ranking are met." @default.
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- W2758358416 date "2017-09-29" @default.
- W2758358416 modified "2023-09-23" @default.
- W2758358416 title "Performance of coefficient of variation estimators in ranked set sampling" @default.
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- W2758358416 doi "https://doi.org/10.1080/00949655.2017.1381959" @default.
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