Two New Parametric Entropic Models for Discrete Probability Distributions
Main Article Content
Abstract
Information theory fundamentally deals with two types of theoretical models frequently well acknowledged as entropy and divergence. In the literature of entropy models for the discrete probability distributions, there survive numerous standard models but still there is possibility that several innovative models can be constructed so as to provide their applications in a variety of disciplines of mathematical sciences. The present communication is a right step in this direction and participates with the derivation of two new parametric models of entropy. Furthermore, it provides the meticulous study of the most advantageous properties of the projected discrete models to prove their legitimacy.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
