Kernel-based estimation of P(X >Y) in ranked set sampling

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TITLE:

Kernel-based estimation of P(X >Y) in ranked set sampling - RP:2447

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https://hdl.handle.net/20.500.11797/RP2447

URV's Author/s:	Zamanzade, Ehsan Mahdizadeh, Mahdi
Journal publication year:	2016
Publication Type:	info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
Abstract:	This article is directed at the problem of reliability estimation using ranked set sampling. A nonparametric estimator based on kernel density estimation is developed. The estimator is shown to be superior to its analog in simple random sampling. Monte Carlo simulations are employed to assess performance of the proposed estimator. Two real data sets are analysed for illustration.
Keywords:	Bandwidth selection, Judgment ranking, Stress-strength model

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Description:	This article is directed at the problem of reliability estimation using ranked set sampling. A nonparametric estimator based on kernel density estimation is developed. The estimator is shown to be superior to its analog in simple random sampling. Monte Carlo simulations are employed to assess performance of the proposed estimator. Two real data sets are analysed for illustration.
Coverage:	eng
Type:	SORT:ART info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
Títol:	Kernel-based estimation of P(X >Y) in ranked set sampling
Subject:	Bandwidth selection, Judgment ranking, Stress-strength model
Format:	application/pdf
Creator:	Zamanzade, Ehsan Mahdizadeh, Mahdi
Date:	2016
Publisher:	Universitat Rovira i Virgili Universitat de Lleida Universitat de Girona Universitat Pompeu Fabra Universitat Politècnica de Catalunya Universitat Autònoma de Barcelona Universitat de Barcelona Institut d'Estadística de Catalunya

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