Bounds on the information divergence for hypergeometric distributions

Lower bounds on Information Divergence

In this paper we establish lower bounds on information divergence from a distribution to certain important classes of distributions as Gaussian, exponential, Gamma, Poisson, geometric, and binomial. These lower bounds are tight and for several convergence theorems where a rate of convergence can be computed, this rate is determined by the lower bounds proved in this paper. General techniques fo...

Exponential bounds for the hypergeometric distribution.

We establish exponential bounds for the hypergeometric distribution which include a finite sampling correction factor, but are otherwise analogous to bounds for the binomial distribution due to León and Perron (Statist. Probab. Lett.62 (2003) 345-354) and Talagrand (Ann. Probab.22 (1994) 28-76). We also extend a convex ordering of Kemperman's (Nederl. Akad. Wetensch. Proc. Ser. A76 = Indag. Mat...

On the quantile transform for asymmetric binomial and hypergeometric distributions

On bounds involving k-Appell’s hypergeometric functions

In this paper, we derive a new extension of Hermite-Hadamard's inequality via k-Riemann-Liouville fractional integrals. Two new k-fractional integral identities are also derived. Then, using these identities as an auxiliary result, we obtain some new k-fractional bounds which involve k-Appell's hypergeometric functions. These bounds can be viewed as new k-fractional estimations of trapezoidal a...

On Classification of Bivariate Distributions Based on Mutual Information

Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...