Prediction for Inverted Topp-Leone Distribution Based on Constant Stress-Partially Accelerated Life Testing

نوع المستند : المقالة الأصلية

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Prediction of future observations on the basis of the past and present information is a fundamental problem of statistics, arising in many contexts and producing varied solutions. The predictor can be either a point or an interval predictor. This paper focuses on predicting the future observations from the inverted Topp-Leone distribution for constant stress-partially accelerated life test based on Type II censored samples. The two-sample prediction is applied to obtain the conditional maximum likelihood, Bayesian and E-Bayesian prediction (point and interval) for future order statistics. The Bayes and E-Bayes predictors are considered under two different loss functions, the balanced squared error loss function; as a symmetric loss function and balanced linear exponential loss function; as an asymmetric loss function. The predictors are obtained based on gamma prior and uniform hyperprior distributions. A numerical example is provided to illustrate the theoretical results and an application using real data sets are used to demonstrate how the results can be used in practice.
 

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