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AuthorAbou Ghaida, Wassim R.
AuthorBaklizi, Ayman
Available date2022-03-10T05:31:34Z
Publication Date2022-01-01
Publication NameInternational Journal of Systems Assurance Engineering and Management
Identifierhttp://dx.doi.org/10.1007/s13198-021-01510-3
CitationAbou Ghaida, W.R., Baklizi, A. Prediction of future failures in the log-logistic distribution based on hybrid censored data. Int J Syst Assur Eng Manag (2022). https://doi.org/10.1007/s13198-021-01510-3
ISSN09756809
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122277087&origin=inward
URIhttp://hdl.handle.net/10576/27886
AbstractWe 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 conditional median, and the maximum likelihood predictors. Prediction intervals were derived using suitable pivotal quantities and intervals based on the highest density. We conducted a simulation study to compare the point and interval predictors. It is found that the point predictor BUP and the prediction interval HDI have the best overall performance. An illustrative example based on real data is given.
SponsorOpen Access funding provided by the Qatar National Library.
Languageen
PublisherSpringer
SubjectHybrid censoring
Log-logistic distribution
Point prediction
Prediction intervals
TitlePrediction of future failures in the log-logistic distribution based on hybrid censored data
TypeArticle
ESSN0976-4348
dc.accessType Open Access


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