Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Ayman Baklizi"'
Autor:
Ayman Baklizi, Sawsan Abu Ghannam
Publikováno v:
Heliyon, Vol 8, Iss 12, Pp e11976- (2022)
Statistical Process Control (SPC) is applied to monitor production processes in order to discover any problems or issues that may arise during the production process and to help in finding solutions for these issues. In this paper, we consider a situ
Externí odkaz:
https://doaj.org/article/9cc560070542493990346cf16cb639d4
Autor:
Ayman Baklizi
Publikováno v:
Symmetry, Vol 14, Iss 11, p 2369 (2022)
We consider inference based on the profile likelihood function for the scale parameter of the generalized logistic distribution. This distribution is a generalization of the logistic distribution, a symmetric distribution like the normal distribution
Externí odkaz:
https://doaj.org/article/7e055ce6b2b64938997506224701a2f5
Autor:
Ayman Baklizi
Publikováno v:
Symmetry, Vol 14, Iss 9, p 1767 (2022)
We consider third-order likelihood inferences for the parameters, quantiles and reliability function of the logistic distribution. This theory involves the conditioning and marginalization of the likelihood function. The logistic distribution is a sy
Externí odkaz:
https://doaj.org/article/0f7ab42f852947629a303cc0f5b77e8e
Autor:
Fatima A. Alshaikh, Ayman Baklizi
Publikováno v:
Mathematics and Statistics. 10:1304-1312
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0cc16fa0bfb90e172c74ff4067c19833
https://doi.org/10.13189/ms.2022.100616
https://doi.org/10.13189/ms.2022.100616
Autor:
Ayman Baklizi, Sawsan Abu Ghannam
Publikováno v:
Journal of Probability and Statistical Science. 20:41-51
This research aims to analyze data coming from step stress life testing experiments where the stress level is incremented at a preset time to obtain failure data faster. To analyze step stress data, a model that extrapolates the information attained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74162c4cc16ebb08e3bec1258b688813
https://doi.org/10.37119/jpss2022.v20i1.512
https://doi.org/10.37119/jpss2022.v20i1.512
Autor:
Ayman Baklizi, Rana Rimawi
Publikováno v:
Asian Journal of Probability and Statistics. :11-23
Generalized distributions have become increasingly popular in applications. They are highly flexible in data analysis, especially with skewed data, which are common in many applications. The Generalized Logistic Distribution (GLD) and its special cas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdedbf3309f69b47d8020a53a84ee074
https://doi.org/10.9734/ajpas/2022/v17i330423
https://doi.org/10.9734/ajpas/2022/v17i330423
Autor:
Ayman Baklizi, Reza Pakyari
Publikováno v:
Computational Statistics. 37:2249-2265
In this article, we propose two goodness-of-fit test statistics for the Burr Type X distribution when the available data are subject to progressively Type-II censoring. The proposed test statistics are based on the sample correlation coefficient betw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b134d9ea5ba55a42bccf9bb1212b2944
https://doi.org/10.1007/s00180-022-01197-5
https://doi.org/10.1007/s00180-022-01197-5
Publikováno v:
Journal of Probability and Statistical Science. 21
A goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::597361136886f147ed499c40d0b369e7
https://doi.org/10.37119/jpss2023.v21i1.663
https://doi.org/10.37119/jpss2023.v21i1.663
Autor:
Maisoun Sewailem, Ayman Baklizi
In this paper, we consider improving maximum likelihood inference for the scale parameter of the Lomax distribution. The improvement is based on using modifications to the maximum likelihood estimator based on the Barndorff-Nielsen modification of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b420c29af851b557c9f2ddc2d78bcda
https://hdl.handle.net/10576/29522
https://hdl.handle.net/10576/29522
Autor:
Wassim R. Abou Ghaida, Ayman Baklizi
We consider the prediction of future observations from the log-logistic distribution. The data is assumed hybrid right censored with possible left censoring. Different point predictors were derived. Specifically, we obtained the best unbiased, the co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b167c2bbd79e007640870ea6cfd4e08c
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122277087&origin=inward
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122277087&origin=inward