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A Simple Estimator of Error Correlation in Non‐parametric Regression Models
Author(s) -
PARK BYEONG U.,
LEE YOUNG KYUNG,
KIM TAE YOON,
PARK CHEOLYONG
Publication year - 2006
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2006.00506.x
Subject(s) - estimator , mathematics , regression function , statistics , parametric statistics , regression , correlation , regression analysis , simple (philosophy) , context (archaeology) , nonparametric regression , bandwidth (computing) , simple linear regression , econometrics , computer science , paleontology , philosophy , geometry , epistemology , biology , computer network
. It is well known that major strength of non‐parametric regression function estimation breaks down when correlated errors exist in the data. Positively (negatively) correlated errors tend to produce undersmoothing (oversmoothing). Several remedies have been proposed in the context of bandwidth selection problem, but they are hard to implement without prior knowledge of error correlations. In this paper we propose a simple estimator of error correlation which is ready to implement and reports a reasonably good performance.