[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Ethics Considerations::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
Indexing and Abstracting



 
..
Social Media

..
Licenses
Creative Commons License
This Journal is licensed under a Creative Commons Attribution NonCommercial 4.0
International License
(CC BY-NC 4.0).
 
..
Similarity Check Systems


..
:: Volume 11, Issue 1 (9-2017) ::
JSS 2017, 11(1): 101-118 Back to browse issues page
The Generalization of Maximum Entropy Principle for Generalized Information Measures
Manije Sanei Tabass , Gholamreza Mohtashami Borzadaran *
Abstract:   (7075 Views)

Maximum of the Renyi entropy and the Tsallis entropy are generalization of the maximum entropy for a larger class of Shannon entropy. In this paper we introduce the maximum Renyi entropy and some of the attributes of distributions which have maximum Renyi entropy investigated. The form of distributions with maximum Renyi entropy is power so we state some properties of these distributions and we have a new form of the Renyi entropy. After pointing the topics of minimum Renyi divergence, some other points in this relation have been discussed. An another form of Renyi divergence have also obtained. Therefore we discussed some of the economic applications of the maximum entropy. Meanwhile, the review of the Csiszar information measure, the general form of distributions with minimum Renyi divergence have obtained.

Keywords: Maximum Entropy, Maximum Renyi Entropy, Maximum Tsallis Entropy, Minimum Renyi Divergence.
Full-Text [PDF 194 kb]   (2611 Downloads)    
Type of Study: Research | Subject: General
Received: 2015/12/7 | Accepted: 2017/09/6 | Published: 2017/12/6
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Sanei Tabass M, Mohtashami Borzadaran G. The Generalization of Maximum Entropy Principle for Generalized Information Measures. JSS 2017; 11 (1) :101-118
URL: http://jss.irstat.ir/article-1-338-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 11, Issue 1 (9-2017) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

Persian site map - English site map - Created in 0.06 seconds with 45 queries by YEKTAWEB 4645