dc.contributor.author | Alma, O. Gurunlu | |
dc.contributor.author | Belaghi, R. Arabi | |
dc.date.accessioned | 2020-11-20T15:02:48Z | |
dc.date.available | 2020-11-20T15:02:48Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 0094-9655 | |
dc.identifier.issn | 1563-5163 | |
dc.identifier.uri | https://doi.org/10.1080/00949655.2015.1025785 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12809/2595 | |
dc.description | WOS: 000364339300010 | en_US |
dc.description.abstract | A progressive hybrid censoring scheme is a mixture of type-I and type-II progressive censoring schemes. In this paper, we mainly consider the analysis of progressive type-II hybrid-censored data when the lifetime distribution of the individual item is the normal and extreme value distributions. Since the maximum likelihood estimators (MLEs) of these parameters cannot be obtained in the closed form, we propose to use the expectation and maximization (EM) algorithm to compute the MLEs. Also, the Newton-Raphson method is used to estimate the model parameters. The asymptotic variance-covariance matrix of the MLEs under EM framework is obtained by Fisher information matrix using the missing information and asymptotic confidence intervals for the parameters are then constructed. This study will end up with comparing the two methods of estimation and the asymptotic confidence intervals of coverage probabilities corresponding to the missing information principle and the observed information matrix through a simulation study, illustrated examples and real data analysis. | en_US |
dc.description.sponsorship | Council Higher Education, TurkeyMinistry of National Education - Turkey | en_US |
dc.description.sponsorship | The first author thanks the Council Higher Education, Turkey for funding this research work and also thanks Professor N. Balakrishnan for his advice and assistance in keeping her progress on schedule. | en_US |
dc.item-language.iso | eng | en_US |
dc.publisher | Taylor & Francis Ltd | en_US |
dc.item-rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Extreme Value Distribution | en_US |
dc.subject | Expectation and Maximization Algorithm | en_US |
dc.subject | Maximum Likelihood Estimators | en_US |
dc.subject | Normal Distribution | en_US |
dc.subject | Newton-Raphson Method | en_US |
dc.subject | Type-II Progressively Hybrid Censoring | en_US |
dc.title | On the estimation of the extreme value and normal distribution parameters based on progressive type-II hybrid-censored data | en_US |
dc.item-type | article | en_US |
dc.contributor.department | MÜ | en_US |
dc.contributor.departmentTemp | [Alma, O. Gurunlu] Mugla Sitki Kocman Univ, Dept Stat, Fac Sci, TR-48000 Mugla, Turkey -- [Belaghi, R. Arabi] Univ Tabriz, Fac Math Sci, Dept Stat, Tabriz, Iran | en_US |
dc.identifier.doi | 10.1080/00949655.2015.1025785 | |
dc.identifier.volume | 86 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.startpage | 569 | en_US |
dc.identifier.endpage | 596 | en_US |
dc.relation.journal | Journal of Statistical Computation and Simulation | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |