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313796

Estimation of Simple Linear Regression Model Parameters Using Double Ranked Set Sampling

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Last updated: 28 Dec 2024

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Abstract

The notion of ranked set sampling (RSS) for estimating the mean of a population and its advantage over the use of a simple random sampling for the same aim is well known and established in the literature. Furthermore, the double ranked set sampling (DRSS), a two-stage RSS, has proven that it is even more efficient than RSS when estimating the mean. In this article, we review the use of the DRSS to estimate the intercept, the slope, and the standard deviation of the error terms as parameters of a simple linear regression model, when replications exist at each value of the predictor. We derive the best linear unbiased estimators of simple linear regression model parameters using the DRSS. Finally, we illustrate the proposed procedure by applying it when the underlying distribution of the error terms is normal or Laplace. Regardless of the assumed number of replications in the experiment, we observe a substantial gain in relative precision while using DRSS procedure over using RSS technique.  

DOI

10.21608/esju.2002.313796

Keywords

Ranked set sampling, Double Ranked Set Sampling, Best Linear Unbiased Estimator, Simple Linear Regression Model, Relative Precision

Volume

46

Article Issue

2

Related Issue

43026

Issue Date

2002-12-01

Publish Date

2002-12-01

Page Start

160

Page End

166

Print ISSN

0542-1748

Online ISSN

2786-0086

Link

https://esju.journals.ekb.eg/article_313796.html

Detail API

https://esju.journals.ekb.eg/service?article_code=313796

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4

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Original Article

Type Code

1,914

Publication Type

Journal

Publication Title

The Egyptian Statistical Journal

Publication Link

https://esju.journals.ekb.eg/

MainTitle

Estimation of Simple Linear Regression Model Parameters Using Double Ranked Set Sampling

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Article

Created At

28 Dec 2024