Parameter estimation of generalized Rayleigh distribution based on ranked set sample


Esemen M., GÜRLER S.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.88, no.4, pp.615-628, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 88 Issue: 4
  • Publication Date: 2018
  • Doi Number: 10.1080/00949655.2017.1398256
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.615-628
  • Keywords: Generalized Rayleigh, maximum likelihood estimation, ranked set sampling, imperfect ranking, relative efficiency, X DISTRIBUTION
  • Dokuz Eylül University Affiliated: Yes

Abstract

Ranked set sampling (RSS) is an efficient method for estimating parameters when exact measurement of observation is difficult and/or expensive. In this paper, we provide maximum likelihood estimation of the shape and scale parameters concerning generalized Rayleigh distribution based on RSS and its some modifications. We compare the biases, mean squared errors and relative efficiencies of estimators in simple random sampling, RSS, extreme RSS and median RSS with different set and cycle sizes. Comparison of the mean squared errors of estimators in RSS for the case of imperfect ranking are also given. Monte Carlo simulation study is performed by using Mathematica 11.0 with 10,000 repetitions.