Bootstrap prediction and tolerance intervals for the Weibull regression model with censored data Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/g445ch80s

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  • The problems of constructing prediction and tolerance intervals were considered for Weibull regression models. On the extreme value distribution scale, the models have the linear form y = Xβ + σ z , =NM where y is the transformed random response vector, X is the nxq matrix containing values of the regressor variables, β is a vector of unknown regression coefficients, σ is an unknown scale parameter and z is a vector of independent standard extreme value distributed error terms. The intervals constructed include two-sided prediction intervals and one-sided tolerance intervals. Further, one-sided confidence bands were developed for percentiles. The interval procedures can be applied for randomly right-censored data or uncensored data. Maximum likelihood estimation was used in the the bootstrap technique for constructing the various intervals. A simulation study was performed to investigate the accuracy of the procedures in complete sample cases. From the simulation study, the bootstrap intervals were found to have accurate confidence levels.
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