Title : ( One-sample Prediction based on Weibull Interval Censored Data )
Authors: Somayeh Ghafouri , Arezou Habibirad ,
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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.
@inproceedings{paperid:1059176,
author = {Ghafouri, Somayeh and Habibirad, Arezou},
title = {One-sample Prediction based on Weibull Interval Censored Data},
booktitle = {سیزدهمین کنفرانس آمار ایران},
year = {2016},
location = {کرمان, IRAN},
keywords = {Approximate maximum likelihood procedure; Bootstrap samples; Interval censoring;
Mean squared prediction error; Monte Carlo simulation; One-sample prediction.},
}
%0 Conference Proceedings
%T One-sample Prediction based on Weibull Interval Censored Data
%A Ghafouri, Somayeh
%A Habibirad, Arezou
%J سیزدهمین کنفرانس آمار ایران
%D 2016
