Residual Verma Entropy of k-Record Values

Verma entropy of k-record values

In this paper, we introduce a new generalization of univariate and bivariate modified discrete Weibull distribution. Various properties of the univariate generalized modified discrete Weibull distribution, such as survival function, probability mass function, hazard rate function, probability generating function, and moment generating function, are derived. The joint distribution function, joint probability mass function, marginal distributions, moment generating function, and conditional distribution of the proposed bivariate distribution are derived. Parameters of the distributions are estimated using maximum likelihood estimation. The use of these distributions is illustrated using real-life datasets.

In this paper, we consider a generalized residual entropy known as residual
Verma entropy(RVE) of k-record values. A representation of RVE of nth krecord value arising from any continuous distribution is expressed in terms of RVE of nth k-record value arising from uniform distribution. We provide bounds for residual Verma entropy of k-record values. Monotone behaviour of RVE of k-record values in terms of number of observations have also been considered.