Ordered extreme ranked set sampling and its application in parametric estimation

Chacko, Manoj

doi:10.2991/jsta.2016.15.3.5

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…Stokes [11] proposed a variant of the ranked set sampling process called extreme ranked set sampling (ERSS), in which only the highest-or lowest-ranked evaluating unit is selected for measurement. As a variant of ERSS, Chacko [12] implemented an ordered extreme ranked set sampling (OERSS) by sorting the ERSS's components by increasing magnitude. Using the MRSS with the unequal samples method, Eskandarzadeh et al [13] investigated information metrics.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples

Hassan,

Alamri

2024

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Sample selection is one of the most important factors in estimating the unknown parameters of distributions, as it saves time, saves effort, and gives the best results. One of the challenges is deciding on a suitable distribution estimate technique and adequate sample selection to provide the best results in comparison with earlier research. The method of moments (MOM) was decided on to estimate the unknown parameters of the Gumbel distribution, but with four changes in the sample selection, which were simple random sample (SRS), ranked set sampling (RSS), maximum ranked set sampling (MRSS), and ordered maximum ranked set sampling (OMRSS) techniques, due to small sample sizes. The MOM is a traditional method for estimation, but it is difficult to use when dealing with RSS modification. RSS modification techniques were used to improve the efficiency of the estimators based on a small sample size compared with the usual SRS estimator. A Monte Carlo simulation study was carried out to compare the estimates based on different sampling. Finally, two datasets were used to demonstrate the adaptability of the Gumbel distribution based on the different sampling techniques.

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Section: Introductionmentioning

confidence: 99%

Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples

Hassan,

Alamri

2024

Axioms

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“…In the literature, a number of studies can be found where efficient estimation of parameters of different bivariate distribution is done using RSS and modified RSS schemes. Some work in this direction is by Al-Saleh and Al-Ananbeh [17] , Chacko and Thomas [18] , Chacko [19] , Lesitha et al [20] , Lesitha and Thomas [8] , Kamalja and Koshti [21] , Koshti and Kamalja [22] , Tahmasebi and Jafari [23] , etc.…”

Section: Introductionmentioning

confidence: 99%

Efficient Estimation of a Scale Parameter of Bivariate Lomax Distribution by Ranked Set Sampling

Koshti

Kamalja

2021

Calcutta Statistical Association Bulletin

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Ranked set sampling (RSS) is an efficient technique for estimating parameters and is applicable whenever ranking on a set of sampling units can be done easily by a judgment method or based on an auxiliary variable. In this paper, we assume [Formula: see text]to have bivariate Lomax distribution where a study variable [Formula: see text]is difficult and/or expensive to measure and is correlated with an auxiliary variable [Formula: see text] which is readily measurable. The auxiliary variable is used to rank the sampling units. In this article, we propose an estimator for the scale parameter of bivariate Lomax distribution using some of the modified RSS schemes. Efficiency comparison of the proposed estimators is performed numerically as well as graphically. A simulation study is also performed to demonstrate the performance of the proposed estimators. Finally, we implement the results to real-life datasets. AMS classification codes: 62D05, 62F07, 62G30

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A review on concomitants of order statistics and its application in parameter estimation under ranked set sampling

Koshti,

Kamalja

2023

J. Korean Stat. Soc.

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Ordered extreme ranked set sampling and its application in parametric estimation

Cited by 5 publications

References 16 publications

Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples

Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples

Efficient Estimation of a Scale Parameter of Bivariate Lomax Distribution by Ranked Set Sampling

A review on concomitants of order statistics and its application in parameter estimation under ranked set sampling

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