Robust estimation for non-homogeneous data and the selection of the optimal tuning parameter: the density power divergence approach

The density power divergence (DPD) measure, defined in terms of a single parameter α, has proved to be a popular tool in the area of robust estimation [ 1 ]. Recently, Ghosh and Basu [ 5 ] rigorously established the asymptotic properties of the MDPDEs in case of independent non-homogeneous observati...

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Bibliographic Details
Published in:	Journal of applied statistics Vol. 42; no. 9; pp. 2056 - 2072
Main Authors:	Ghosh, Abhik, Basu, Ayanendranath
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 02.09.2015 Taylor & Francis Ltd
Subjects:	Asymptotic methods Density density power divergence Divergence linear regressionmodel Mathematical models non-homogeneous data Optimization Parameter estimation Parameter optimization Primary: 62F35 Regression Regression analysis Robustness Secondary: 62J05 Studies Tuning tuning parameter
ISSN:	0266-4763, 1360-0532
Online Access:	Get full text
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