The exponentiated generalized power Lindley distribution: Properties and applications

In this paper, we introduce a new extension of the power Lindley distribution, called the exponentiated generalized power Lindley distribution. Several mathematical properties of the new model such as the shapes of the density and hazard rate functions, the quantile function, moments, mean deviations, Bonferroni and Lorenz curves and order statistics are derived.Moreover, we discuss the parameter estimation of the new distribution using the maximum likelihood and diagonally weighted least squares methods. A simulation study is performed to evaluate the estimators. We use two real data sets to illustrate the applicability of the new model. Empirical findings show that the proposed model provides better fits than some other well-known extensions of Lindley distributions.     

Nonparametric prediction intervals for future record intervals based on order statistics

In this article, outer and inner prediction intervals for future record intervals as well as record spacings are derived based on observed order statistics from the same parent distribution. These intervals are exact and are distribution-free in that they do not depend on the sampling distribution. Three different cases are considered and in each case an exact explicit expression is obtained for the prediction coefficient. Finally, we compare the obtained results with similar intervals based on records, and also present a numerical example in order to illustrate the derived results.