More powerful permutation test based on multistage ranked set sampling

Amro, Lubna; Samuh, Monjed H.

doi:10.1080/03610918.2016.1152364

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Finally, we believe that it would be very useful to evaluate inferential procedures based on intensive simulation methods, as alternatives to analytical and/or asymptotically results, using, for example, randomization and resampling techniques. There are still few studies addressing these procedures in the RSS literature, among which we can cite Modarres et al (2006), regarding resampling methods in RSS, and Amro and Samuh (2017), for permutation tests in multistage ranked set sampling.…”

Section: Discussionmentioning

confidence: 99%

On the performance of estimation methods under ranked set sampling

Taconeli

Bonat

2020

Comput Stat

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Maximum likelihood estimation (MLE) applied to ranked set sampling (RSS) designs is usually based on the assumption of perfect ranking. However, it may suffers of lack of efficiency when ranking errors are present. The main goal of this article is to investigate the performance of six alternative estimation methods to MLE for parameter estimation under RSS. We carry out an extensive simulation study and measure the performance of the maximum product of spacings, ordinary and weighted least-squares, Cramér-von-Mises, Anderson-Darling and right-tail Anderson-Darling estimators, along with the maximum likelihood estimators, through the Kullback-Leibler divergence from the true and estimated probability density functions. Our simulation study considered eight continuous probability distributions, six sample sizes and six levels of correlation between the interest and concomitant variables. In general, our results show that the Anderson-Darling method outperforms its competitors and that the maximum likelihood estimators strongly depends on perfect ranking for accurate estimation. Finally, we present an illustrative example using a data set concerning the percent of body fat. R code is available in the supplementary material.

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Section: Discussionmentioning

confidence: 99%

On the performance of estimation methods under ranked set sampling

Taconeli

Bonat

2020

Comput Stat

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“…For example, [7] studied Weibull and Pareto distributions, [8] introduced the maximum likelihood estimation of the modified Weibull distribution parameters using extreme ranking set sampling, [9], [10] and [11].and a -stage RSS design uses +1 sample units from the target population to produce a sample of size after stages of ranking developed [12]. For more details, see [13], [14], [15] and [16], see more [17], [18] and [19].…”

Section: Figure 1 Pdf Of the Epgw Distribution For Different Parameter Valuesmentioning

confidence: 99%

On Maximum Likelihood Estimators of the Parameters of Three-Parameters Weibull Distribution Using Different Ranked Set Sampling Schemes

Aziz¹,

Shaaban²

2021

CRPASE

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Al-Saleh and Al-Kadiri first proposed double rank set sampling (DRSS). It seems that this ranked set sampling (RSS) modification can reduce the loss of RSS efficiency caused by ranking errors, and it is more effective than RSS and simple random sampling (SRS) to estimate the population mean. The proposed likelihood function is used to estimate the parameters of the three-Parameters Weibull distribution. Based on double ranked set sampling, extreme ranked set sampling, ranked set sampling (RSS) and simple random sampling (SRS) designs, the maximum likelihood estimator (MLE) is compared with the corresponding likelihood estimator. A simulation was carried out and the absolute relative biases, mean square error (MSE) and relative efficiency of different schemes were compared. It is found that, MSEs based SRS data has the largest MSEs comparing to RSS and its modifications schemes. This study revealed that DRSS technique has the superior over the rest of other sampling schemes. In almost all cases, DRSS has the smallest MSEs and largest efficiencies.

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Ranked Set Two-Sample Permutation Test

Samuh

2018

Statistica

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More powerful permutation test based on multistage ranked set sampling

Cited by 4 publications

References 25 publications

On the performance of estimation methods under ranked set sampling

On the performance of estimation methods under ranked set sampling

On Maximum Likelihood Estimators of the Parameters of Three-Parameters Weibull Distribution Using Different Ranked Set Sampling Schemes

Ranked Set Two-Sample Permutation Test

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