A Characterization of All Single-Integral, Non-Kernel Divergence Estimators

Divergence measures have been used for a long time for different purposes in information theory and statistics. In particular, density-based minimum divergence estimation is a popular tool in the statistical literature. Given the sampled data and a parametric model, we estimate the model parameter b...

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Bibliographic Details
Published in:	IEEE transactions on information theory Vol. 65; no. 12; pp. 7976 - 7984
Main Authors:	Jana, Soham, Basu, Ayanendranath
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.12.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Bandwidth Bregman divergence characterization Data models Density Divergence Estimation Information theory Kernel Kernels Mathematical model non-kernel divergence Parameter estimation Robustness single-integral Smoothing Smoothing methods
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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