Different classical estimation methods using ranked set sampling and data analysis for the inverse power Cauchy distribution

Hassan, Amal S.; Alsadat, Najwan; Elgarhy, Mohammed; Chesneau, Christophe; Elmorsy Mohamed, Rokaya

doi:10.1016/j.jrras.2023.100685

Cited by 3 publications

(1 citation statement)

References 61 publications

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“…Furthermore, additional studies are needed to address the theoretical properties of the proposed estimators. Moreover, examining the parametric inference, see Hassan et al (2023)…”

Section: Discussionmentioning

confidence: 99%

Valid estimation of the distribution function using dual-rank ranked set sampling: Missing data approach

Abdallah

2024

The Egyptian Statistical Journal

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In this study, two nonparametric estimators of estimating distribution function under dual-rank ranked set sampling (DRSS) are discussed and compared. The first estimator incorporates the information supported by the relationship between ranks of measured sampling items and information from unmeasured sampling items. This estimator is constructed through an iterative algorithm. The second one depends on using the information generated by a concomitant variable. This estimator is derived by the linear interpolation method. Under both perfect and imperfect ranking situations, a series of simulation studies are carried out, and the proposed estimators are then compared with their counterparts using traditional ranked set sampling (RSS). It is concluded that the proposed procedures have dramatically better performance than their competitors at points in the center of the parent distribution, specifically in the case of an appropriate level of ranking quality. Finally, an illustrative example using a real dataset is also used to investigate the performance of the proposed procedures.

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“…Furthermore, additional studies are needed to address the theoretical properties of the proposed estimators. Moreover, examining the parametric inference, see Hassan et al (2023)…”

Section: Discussionmentioning

confidence: 99%

Valid estimation of the distribution function using dual-rank ranked set sampling: Missing data approach

Abdallah

2024

The Egyptian Statistical Journal

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Estimation methods based on ranked set sampling for the power logarithmic distribution

Alsadat,

Hassan,

Elgarhy

et al. 2024

Sci Rep

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The sample strategy employed in statistical parameter estimation issues has a major impact on the accuracy of the parameter estimates. Ranked set sampling (RSS) is a highly helpful technique for gathering data when it is difficult or impossible to quantify the units in a population. A bounded power logarithmic distribution (PLD) has been proposed recently, and it may be used to describe many real-world bounded data sets. In the current work, the three parameters of the PLD are estimated using the RSS technique. A number of conventional estimators using maximum likelihood, minimum spacing absolute log-distance, minimum spacing square distance, Anderson-Darling, minimum spacing absolute distance, maximum product of spacings, least squares, Cramer-von-Mises, minimum spacing square log distance, and minimum spacing Linex distance are investigated. The different estimates via RSS are compared with their simple random sampling (SRS) counterparts. We found that the maximum product spacing estimate appears to be the best option based on our simulation results for the SRS and RSS data sets. Estimates generated from SRS data sets are less efficient than those derived from RSS data sets. The usefulness of the RSS estimators is also investigated by means of a real data example.

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Estimation methods based on ranked set sampling for the arctan uniform distribution with application

Alyami,

Hassan,

Elbatal

et al. 2024

MATH

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<abstract><p>The arctan uniform distribution (AUD) is a brand-new bounded distribution that may be used for modeling a variety of existing bounded real-world datasets. Ranked set sampling (RSS) is a useful technique for parameter estimation when accurate measurement of the observation is challenging and/or expensive. In the current study, the parameter estimator of the AUD is addressed based on RSS and simple random sampling (SRS) techniques. Some of the popular conventional estimating techniques are considered. The efficiency of the produced estimates is compared using a Monte Carlo simulation. It appears that the maximum product spacing method has an advantage in assessing the quality of proposed estimates based on the outcomes of our simulations for both the SRS and RSS datasets. In comparison to estimates produced from the SRS datasets, it can be seen that those from the RSS datasets are more reliable. This implies that RSS is a more effective sampling technique in terms of generating estimates with a smaller mean squared error. The benefit of the RSS design over the SRS design is further supported by real data results.</p></abstract>

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Different classical estimation methods using ranked set sampling and data analysis for the inverse power Cauchy distribution

Cited by 3 publications

References 61 publications

Valid estimation of the distribution function using dual-rank ranked set sampling: Missing data approach

Valid estimation of the distribution function using dual-rank ranked set sampling: Missing data approach

Estimation methods based on ranked set sampling for the power logarithmic distribution

Estimation methods based on ranked set sampling for the arctan uniform distribution with application

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