Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring

機構典藏 > College of Business and Management > Graduate Institute & Department of Statistics > Journal Article > Item 987654321/116856

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/116856

Title:	Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring
Authors:	Shu-Fei Wu;Jin-Yang Lu
Keywords:	Progressive type I interval censored sample;Pareto distribution;Maximum likelihood estimator;Process capability indices
Date:	2017-06
Issue Date:	2019-06-15 12:10:29 (UTC+8)
Publisher:	Springer Berlin Heidelberg
Abstract:	Process capability indices had been widely used to evaluate the process performance to the continuous improvement of quality and productivity. When the lifetime of products possesses a one-parameter Pareto distribution, the larger-the-better lifetime performance index is considered. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also investigated. We use this estimator to develop the new hypothesis testing algorithmic procedure in the condition of known lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.
Relation:	Computational Statistics 32(2), p.647–666
DOI:	10.1007/s00180-017-0717-3
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

Files in This Item:

File	Description	Size	Format
Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring.pdf		681Kb	Adobe PDF	1	View/Open
index.html		0Kb	HTML	136	View/Open