Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/6672
Title: Minimum distance regression-type estimates with rates under weak dependence
Authors: Roussas, George G. 
Yatracos, Yannis G. 
Roussas, George G. 
Keywords: Regression analysis;Entropy;Estimation
Issue Date: 1996
Publisher: Springer Link
Source: Annals of the Institute of Statistical Mathematics, 1996, Volume 48, Issue 2, Pages 267-281
Abstract: Under weak dependence, a minimum distance estimate is obtained for a smooth function and its derivatives in a regression-type framework. The upper bound of the risk depends on the Kolmogorov entropy of the underlying space and the mixing coefficient. It is shown that the proposed estimates have the same rate of convergence, in the L 1-norm sense, as in the independent case.
URI: http://ktisis.cut.ac.cy/handle/10488/6672
ISSN: 0020-3157 (print)
1572-9052 (online)
DOI: 10.1007/BF00054790
Type: Article
Appears in Collections:Άρθρα/Articles

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