سیزدهمین کنفرانس آمار ایران , 2016-08-23

Title : ( One-sample Prediction based on Weibull Interval Censored Data )

Authors: Somayeh Ghafouri , Arezou Habibirad ,

Access to full-text not allowed by authors

Citation: BibTeX | EndNote

Abstract

Interval censored data arise when a failure time say, Y cannot be observed directly but can only be determined to lie in an interval obtained from a series of inspection times. Therefore, prediction of unobserved Y can be interesting issue. In this paper, we will obtain the approximate maximum likelihood estimators (AMLEs) of unknown parameters in the Weibull distribution and using them, we introduce a point predictor of Y in the ith interval, as the expected value of the conditional distribution of Y given L and R. In addition, using the AMLEs of Weibull parameters, the predictor of Y and percentile bootstrap, we will get the 95% confidence bounds of unkown parameters as well as 95% prediction bound of Y in the ith interval. A Monte Carlo simulation study and an illustrative example presented to assess the proposed performance of the procedures.

Keywords

, Approximate maximum likelihood procedure, Bootstrap samples, Interval censoring, Mean squared prediction error, Monte Carlo simulation, One-sample prediction.