An Efficient CDF Estimator Based on Dual-Rank Ranked Set Sampling with an Application to Body Mass Index Data

Abdallah, Mohamed S.; Al-Omari, Amer I.

doi:10.1007/s41096-023-00171-8

Cited by 1 publication

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further, DRSS requires performing the ranking process twice to be more sensitive to the error ranking relative to RSS. It is worth mentioning that additional comparisons are performed between the proposed procedures and 𝐹 ̂𝐷(𝑡) proposed by Abdallah and Al-Omari (2024). It turns out that the proposed procedures uniformly outperform the latter.…”

Section: Monte Carlo Comparisonsmentioning

confidence: 99%

See 1 more Smart Citation

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

Abdallah

2024

The Egyptian Statistical Journal

View full text Add to dashboard Cite

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.

show abstract

Section: Monte Carlo Comparisonsmentioning

confidence: 99%

“…Taconeli (2023) investigated numerically that DRRSS enables us to estimate the population mean with higher efficiency and precision than RSS, specifically when the parent distribution is symmetric. Abdallah and Al-Omari (2024) used DRRSS to propose a new CDF estimator based on the empirical distribution function given by:…”

Section: The Drrss Schemementioning

confidence: 99%

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

Abdallah

2024

The Egyptian Statistical Journal

View full text Add to dashboard Cite

show abstract

An Efficient CDF Estimator Based on Dual-Rank Ranked Set Sampling with an Application to Body Mass Index Data

Cited by 1 publication

References 16 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

Contact Info

Product

Resources

About