Moving extreme ranked set sampling for simple linear regression

digital

Article

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

Moving extreme ranked set sampling for simple linear regression

Authors

N.A. Al-Odat, M. Al-Rawwash, Mohd T. Alodat, T.T. Alodat

Publisher

Vita e Pensiero

Format

Article |

Pdf

Online from

02-2009

Issn

1824-6672 (print) | 2283-6659 (digital)

Write a comment for this product

Download

Ebook format Pdf readable on these devices:

Computer
with Software:
- Adobe PDF Reader
Android
iPhone/Ipad
with App:
- Adobe PDF Reader
E-Book Reader
Ibs Tolino
Kobo

Description Readers' comments

The moving extreme ranked set sampling, introduced by Alodat and Al-Saleh (2001), is a modification of the well known ranked set sampling approach that was proposed by McIntyre (1952). In this paper, we suggest new estimators for the simple linear regression parameters under the moving extreme ranked set sampling scheme. Moreover, we show that the proposed estimators are more efficient than their counterparts using the simple random sampling approach. We illustrate our ideas and thoughts via simulation and data analysis and conduct a comparison between our approach and the traditional ones. Keywords: Moving ranked set sampling, Ranked set sampling, Simple linear regression.

Enter a comment for Moving extreme ranked set sampling for simple linear regression