On Two Novel Applications of Ranked Set Sampling

2003 ◽  
Vol 54 (1-2) ◽  
pp. 105-114
Author(s):  
Sukuman Sarikavanij ◽  
Montip Tiensuw
Keyword(s):  
Case Studies ◽  
Random Sample ◽  
Ranked Set Sampling ◽  
Simple Random Sample ◽  
Single Family ◽  
Ranked Set Sample ◽  
Population Mean ◽  
Sales Data ◽  
Tree Data ◽  
Novel Applications

In this paper we discuss two case studies which clearly indicate the advantages of using a ranked set sample (RSS) over those of a simple random sample (SRS). The applications of RSS considered here cover single family homes sales data, and tree data. It is demonstrated that in each case RSS is much more efficient than SRS for estimation of population mean.

On the Efficiency of Ranked Set Sampling Strategies in Parametric Estimation

1997 ◽  
Vol 47 (1-2) ◽  
pp. 23-42 ◽  
Author(s):  
Dayong Li ◽  
Nora Ni Chuiv
Keyword(s):  
Random Sample ◽  
Ranked Set Sampling ◽  
Parametric Estimation ◽  
Simple Random Sample ◽  
Sampling Strategies ◽  
Ranked Set Sample ◽  
Estimation Problems ◽  
Parameters Of Interest

In this paper we discuss the issue of efficiency of a ranked set sample compared to a simple random sample in the context of a variety of parametric estimation problems. We establish that the use of appropriate variations of a ranked set sample often results in improved estimation of many common parameters of interest with a substantially smaller number of measurements compared to a simple random sample.

scholarly journals Effectivity of Modified Maximum Likelihood Estimators Using Selected Ranked Set Sampling Data

2016 ◽  
Vol 38 (2) ◽  
Author(s):  
Tamanna Islam ◽  
Molla Rahman Shaibur ◽  
S.S. Hossain
Keyword(s):  
Maximum Likelihood ◽  
Ranked Set Sampling ◽  
Simple Random Sample ◽  
Exponential Distributions ◽  
Underlying Distribution ◽  
Population Mean ◽  
Scale Parameters ◽  
Modified Maximum Likelihood ◽  
Two Parameter ◽  
Better Than

This paper describes the modified maximum likelihood estimator (MMLE) of location and scale parameters based on selected ranked set sampling (SRSS) for normal, uniform and two-parameter exponential distributions. For these distributions, the MMLE of location and scale parameters for SRSS data were compared with the estimators of location and scale parameters for simple random sample (SRS) and ranked set sample (RSS). The MMLE based on SRSS data were found to be advantageous as compared to SRS and RSS estimators for the same number of measurements. The SRSS method with errors in ranking was also described. The minimum correlation between the actual and erroneous ranking was required for MMLE of SRSS to achieve better precision than usual SRS and RSS estimators. When the wrong assumption about the underlying distribution was present, the MMLE of the population mean based on SRSS was better than the RSS estimator ofthe population mean for all the cases considered.

Use OE Ranked Set Sampling for Test of a Normal Mean

1994 ◽  
Vol 44 (3-4) ◽  
pp. 183-194 ◽  
Author(s):  
Wei-Hsiung Shen
Keyword(s):  
Random Sample ◽  
Unbiased Estimator ◽  
Population Distribution ◽  
Simple Random Sample ◽  
Sample Mean ◽  
Ranked Set Sample ◽  
Normal Test ◽  
Normal Mean ◽  
Normal Variance ◽  
Better Than

In situations where the experimental or sampling units in a study can be easily ranked than quantified, Mcintyre (1952) proposed the notion of a ranked set sample ( RSS), and observed that, to estimate the population mean, the sample mean based on a RSS sample of size n provides an unbiased estimator with a smaller variance compared to a simple random sample mean of the same size n. Mcintyre's concept of RSS is essentially nonparametric in nature in that the underlying population distribution is assumed to be completely unknown. Sinha et al. (1992) in a recent paper further explored the concept of RSS and its many variations for estimation of a normal mean and a normal variance, and an exponential mean. In this paper we use the concept of RSS to derive tests for a normal mean μ when the variance is known, and show that many improved tests can be constructed, all of which are much better than the traditional normal test. All our tests are based on the improved eetimators of μ derived in Sinha et. al. (1992).

scholarly journals Efficient Estimation of the Generalized Quasi-Lindley Distribution Parameters under Ranked Set Sampling and Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Amer Ibrahim Al-Omari ◽  
SidAhmed Benchiha ◽  
Ibrahim M. Almanjahie
Keyword(s):  
Least Squares ◽  
Random Sample ◽  
Simulation Study ◽  
Real Data ◽  
Ranked Set Sampling ◽  
Efficient Estimation ◽  
Estimation Methods ◽  
Simple Random Sample ◽  
Lindley Distribution ◽  
Study Results

Ranked set sampling is a very useful method to collect data when the actual measurement of the units in a population is difficult or expensive. Recently, the generalized quasi-Lindley distribution is suggested as a new continuous lifetime distribution. In this article, the ranked set sampling method is considered to estimate the parameters of the generalized quasi-Lindley distribution. Several estimation methods are used, including the maximum likelihood, the maximum product of spacings, ordinary least squares, weighted least squares, Cramer–von Mises, and Anderson–Darling methods. The performance of the proposed ranked set sampling based estimators is achieved through a simulation study in terms of bias and mean squared errors compared to the simple random sample. Additional results are obtained based on real data for the survival times of 72 guinea pigs and 23 ball bearings. The simulation study results and the real data applications showed the superiority of the proposed ranked set sampling estimators compared to the simple random sample competitors based on the same number of measuring units.

scholarly journals Estimation of Population Mean by Using a Generalized Family of Estimators Under Classical Ranked Set Sampling

2021 ◽  
Vol 8 (1) ◽  
pp. 1948184
Author(s):  
Asad Ali ◽  
Muhammad Moeen Butt ◽  
Kanwal Iqbal ◽  
Muhammad Hanif ◽  
Muhammad Zubair
Keyword(s):  
Ranked Set Sampling ◽  
Population Mean

PREFERENSI PENGUNJUNG TERHADAP PELAYANAN DI GRHATAMA PUSTAKA YOGYAKARTA

Pringgitan ◽  
2020 ◽  
Vol 1 (02) ◽  
pp. 87-97
Author(s):  
Sabda Elisa Priyanto ◽  
Eko Sugiarto
Keyword(s):  
Service Quality ◽  
Random Sample ◽  
Sampling Method ◽  
Descriptive Study ◽  
Simple Random Sample ◽  
Library Services ◽  
Key Word ◽  
Recreation Area ◽  
Sample Technique ◽  
Visitor Preferences

The purpose of this paper is to describe the preferences of visitors to the service quality at Grhtama Pustaka Yogyakarta. The library has a function as a place of recreation that should be able to provide good services to visitors. The services provided must be based on visitor preferences when visiting and getting services. Visitor preferences for service quality that is tangible, reliability, responsiveness, assurance, and empathy. Grhtama Pustaka as the largest library in Yogyakarta must be able to provide good services, as a form of support to become a place of recreation in Yogyakarta.  The method in this research is a descriptive study, with a population of visitors to Grhatama Pustaka, selected by the probability sampling method with a simple random sample technique, by interviewing 118 visitors. The results of this study found that tourist preferences for services in Grhatama Pustaka in the tangible part are strong preferences for visitors to visit, while the reliability, responsiveness, assurance, and empathy factors in library services are good preferences for visitors who need library services. Furthermore, hospitality services are needed if the manager wants to make visitors make Grhatama Pustaka a choice of the recreation area. Key Word: Preference, Visitor, Service Quality, Library

scholarly journals A TOOL CONSTRUCTION AND STANDARDIZATION OF NUTRITION KNOWLEDGE OF HIGH SCHOOL STUDENTS

2017 ◽  
Vol 5 (5(SE)) ◽  
pp. 69-74
Author(s):  
T.Indumathi ◽  
N. Ramakrishnan
Keyword(s):  
High School ◽  
High School Students ◽  
Random Sample ◽  
Nutrition Knowledge ◽  
Simple Random Sample ◽  
School Students ◽  
Final Study ◽  
Sample Technique ◽  
Knowledge Scale

In the present study, Nutrition knowledge scale has been constructed and standardized of the High School Students. This scale consists of 54 statements. The simple random sample technique was used for this study. The sample consists of 50 High School Students are randomly selected from the Kancheepuram Districts. The ‘t’ value was sued to standardize the tool and finally 29 statements were retained for the final study.

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