DocumentCode
773227
Title
Information-theoretic approach to unimodal density estimation
Author
Brockett, Patrick L. ; Charnes, A. ; Paick, Kwang H.
Author_Institution
Center for Cybern. Studies, Texas Univ., Austin, TX, USA
Volume
41
Issue
3
fYear
1995
fDate
5/1/1995 12:00:00 AM
Firstpage
824
Lastpage
829
Abstract
Extends the maximum entropy information-theoretic density estimation method to provide a technique which guarantees that the resulting density is unimodal. The method inputs data in the form of moment or quantile constraints and consequently can handle both data-derived and non-data-derived information
Keywords
maximum entropy methods; parameter estimation; probability; data-derived information; information-theoretic approach; maximum entropy; moment constraints; nondata-derived information; probability density distribution; quantile constraints; unimodal density estimation; Bayesian methods; Computer science; Cybernetics; Data engineering; Entropy; Estimation theory; Information analysis; Kernel; Probability density function; Statistical distributions;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.382035
Filename
382035
Link To Document