A measure of inaccuracy in concomitants of ordered random variables under Farlie-Gumbel-Morgenstern family

Abstract

In communication theory, for possible outcomes of an experiment, we have two basic problems for the statement of the experimenter: we may not have enough information (vague statement) or some of the information may be incorrect, which make inaccurate in either or both of these situations. In this article, a measure of inaccuracy and its residual between distributions of concomitants of generalized order statistics ( os) and parent random variable are extended. Results of inaccuracy for family distributions and stochastic comparisons are obtained. Furthermore, some properties of the proposed measure are discussed. The unique characterization of the distribution function of parent random variable by the inaccuracy is shown.

Some properties of cumulative extropy and its dynamic past version

“…Moreover, we concluded that the suggested estimators are influenced by sample size and almost give the same behavior in the simulation procedure. In future work, we can extend the obtained models for ordered variables and their concomitants, for more details see [19,20].…”

Residual and Past Discrete Tsallis and Renyi Extropy with an Application to Softmax Function

“…Finally, we can apply those models to ordered variables and their concomitants for future work. For more details, see [ 17 , 18 , 19 ]. For applications, see [ 20 , 21 , 22 ].…”

Some new findings on the survival Rényi entropy and application of COVID-19 data

“…In addition, they have almost the same value. In future work, we can extend this work to various types of measures such as Tsallis entropy; for more details, see [18] , [19] , [20] , [21] , [22] , [23] , [24] .…”