The purpose of this paper is to obtain the tracking interval for difference of expected Kullback-Leibler risks of two models under Type II hybrid censoring scheme. This interval helps us to evaluate proposed models in comparison with each other. We drive a statistic which tracks the difference of expected Kullback–Leibler risks between maximum likelihood estimators of the distribution in two diff...

The motivation for fractional integration in terms of low-frequency spectral behavior and long-lag autocorrelation behavior is well known. Using results on the rate of growth of variances of sums of integrated random variables, we provide additional and complementary time-domain motivation for fractional integration in terms of the long-horizon behavior of (1) the variance-time function, and (2...

In this paper, we discuss the prediction problem based on censored coherent system lifetime data when the system structure is known and the component lifetime follows the proportional reversed hazard model. Different point and interval predictors based on classical and Bayesian approaches are derived. A numerical example is presented to illustrate the prediction methods used in this paper. Mont...

‎ In many experiments, such as biology and quality control problems, sample size cannot always be considered as a constant value. Therefore, the problem of predicting future data when the sample size is an integer-valued random variable can be an important issue. This paper describes the prediction problem of future order statistics based on upper and lower records. Two different cases for the ...

In this paper, a one-sample point predictor of the random variable X is studied. X is the occurrence of an event in any successive visits $L_i$ and $R_i$ :i=1,2…,n (interval censoring). Our proposed method is based on finding the expected value of the conditional distribution of X given $L_i$ and $R_i$ (i=1,2…,n). To make the desired prediction, our approach is on the basis of approximating the...

This paper presents a novel approach to identify the prediction interval associated with data using type-2 fuzzy logic systems support vector regression. For such purpose, constrained quadratic objective function is defined which then solved well-established programming approaches. Not only does output of system replicates measured value, but also it provides lower bound and upper for values. I...