Bias reduction via linear combination of nearest neighbour entropy estimators
by Alexei Kaltchenko, Nina Timofeeva
International Journal of Information and Coding Theory (IJICOT), Vol. 1, No. 1, 2009

Abstract: The problem of entropy estimation of stationary ergodic processes is considered. A new family of entropy estimators is constructed as a linear combination of the nearest neighbour estimators with a new metric. The consistency of the new estimators is established for the broad class of measures. The O (n^−b)-efficiency of these estimators is established for symmetric probability measures, where b > 0 is a constant and n is the number of observations.

Online publication date: Tue, 24-Mar-2009

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Coding Theory (IJICOT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com