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Characterisation of some generalised continuous distributions by doubly truncated moments

Athar Haseeb, Ahsanullah Mohammad, Ali Mohd. Almech

Operations Research and Decisions

2023

Vol. 33, No. 1

1--19

The characterisation of probability distribution plays an important role in statistical studies. There are various methods of characterisation available in the literature. The characterisation using truncated moments limits the observations; hence, researchers may save time and cost. In this paper, the characterisation of three general forms of continuous distributions based on doubly truncated moments has been studied. The results are given simply and explicitly. Further, the results have been applied to some well-known continuous distributions.

On the characterisation of X-Lindley distribution by truncated moments. Properties and application

Metiri Farouk, Zeghdoudi Halim, Ezzebsa Abdelali

Operations Research and Decisions

2022

Vol. 32, No. 1

99--109

Several papers introduce the new distributions and their applications, including, among others, those of Ducey and Gove [7], Grine and Zeghdoudi [8], Chouia et al. [5], Seghier et al. [11], Beghriche and Zeghdoudi [4], where characterisation of a probability distribution plays an important role in statistical science. Several researchers studied the characterisations of probability distributions. For example, Su and Huang [12] study the characterisations of distributions based on expectations. In addition, Nanda [10] studies the characterisations by average residual life and the failure rates of functions of absolutely continuous random variables. Ahmadi et al. [1] consider the estimation based on the left-truncated and right randomly censored data arising from a general family of distributions. On the other hand, Ahsanullah et al. [2, 3] present two characterisations of Lindley distribution, standard normal distribution, t-Student’s, exponentiated exponential, power function, Pareto, and Weibull distributions based on the relation of failure rate, reverse failure rate functions with left and right truncated moments. Recently, Haseeb and Yahia [9] studied truncated moments for two general classes of continuous distributions. In this paper, two characterisations of the X-Lindley distribution, introduced by Chouia and Zeghdoudi [5] have been studied. They are based on the failure, relation of the inverse failure rate functions with the left and right truncated moments, respectively. Section 2 gives some properties of X-Lindley distribution. Section 3 discusses the characterisation of general distribution by left truncated and failure rate function and then right truncated and reverse failure rate function. Section 4 studies the characterisation of X-Lindley distribution by using the relation between left/right truncated moment and failure/reverse failure rate function. Finally, an illustrative example of X-Lindley distribution with other one-parameter distributions is given to show the superiority and flexibility of this model.