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المؤلفAbou Ghaida, Wassim R.
المؤلفBaklizi, Ayman
تاريخ الإتاحة2022-03-10T05:31:34Z
تاريخ النشر2022-01-01
اسم المنشورInternational Journal of Systems Assurance Engineering and Management
المعرّفhttp://dx.doi.org/10.1007/s13198-021-01510-3
الاقتباسAbou 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
الرقم المعياري الدولي للكتاب09756809
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122277087&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/27886
الملخصWe 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.
راعي المشروعOpen Access funding provided by the Qatar National Library.
اللغةen
الناشرSpringer
الموضوعHybrid censoring
Log-logistic distribution
Point prediction
Prediction intervals
العنوانPrediction of future failures in the log-logistic distribution based on hybrid censored data
النوعArticle
ESSN0976-4348
dc.accessType Open Access


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