Using a conditional method, explicit formulae for computing quantiles pertinent to prediction intervals for future Weibull order statistics are developed for two cases: when only previous independent failure data are available, and when both previous independent failure data and early-failure data in current experiment are available. The second case includes the case when only current early-failure data are available. Comparisons of interval widths are made for different estimators of parameters and different ways of forming prediction intervals
Empirical prediction intervals are constructed based on the distribution of previous out-of-sample f...
In many different contexts, decision making is improved by the availability of probabilistic predict...
Prediction intervals are needed to quantify prediction uncertainty in, for example, warranty predict...
Abstract: Using a conditional method, explicit formulae for computing quantiles pertinent to predict...
In recent years, a new class of models has been proposed to exhibit the bathtub-shaped failure rate ...
AbstractWhen a system consisting of independent components of the same type, some appropriate action...
We study the problem of predicting future records based on observed order statistics from two parame...
This article provides a method using the probability papers for point and interval predictions of fu...
Graduation date:1986Prediction intervals for an outcome of a sufficient statistic, T[subscript y], a...
In the regression framework, prediction intervals are a valuable tool to estimate the value of the r...
[[abstract]]In the researching of products' reliability, the result of life testing is used as the b...
This article proposes a simple method of constructing predictors of future order statistics based on...
We propose a robust method for constructing conditionally valid prediction intervals based on models...
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Syste...
This article evaluates exact coverage probabilities of approximate prediction intervals for the numb...
Empirical prediction intervals are constructed based on the distribution of previous out-of-sample f...
In many different contexts, decision making is improved by the availability of probabilistic predict...
Prediction intervals are needed to quantify prediction uncertainty in, for example, warranty predict...
Abstract: Using a conditional method, explicit formulae for computing quantiles pertinent to predict...
In recent years, a new class of models has been proposed to exhibit the bathtub-shaped failure rate ...
AbstractWhen a system consisting of independent components of the same type, some appropriate action...
We study the problem of predicting future records based on observed order statistics from two parame...
This article provides a method using the probability papers for point and interval predictions of fu...
Graduation date:1986Prediction intervals for an outcome of a sufficient statistic, T[subscript y], a...
In the regression framework, prediction intervals are a valuable tool to estimate the value of the r...
[[abstract]]In the researching of products' reliability, the result of life testing is used as the b...
This article proposes a simple method of constructing predictors of future order statistics based on...
We propose a robust method for constructing conditionally valid prediction intervals based on models...
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Syste...
This article evaluates exact coverage probabilities of approximate prediction intervals for the numb...
Empirical prediction intervals are constructed based on the distribution of previous out-of-sample f...
In many different contexts, decision making is improved by the availability of probabilistic predict...
Prediction intervals are needed to quantify prediction uncertainty in, for example, warranty predict...