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Robust kernel estimators for additive models with dependent observations
Author(s) -
Bianco Ana,
Boente Graciela
Publication year - 1998
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315508
Subject(s) - estimator , kernel (algebra) , econometrics , mathematics , kernel smoother , statistics , computer science , kernel method , artificial intelligence , radial basis function kernel , support vector machine , combinatorics
Robust nonparametric estimators for additive regression or autoregression models under an α‐mixing condition are proposed. They are based on local M ‐estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, diese local M ‐estimators achieve the same univariate rate of convergence as their linear relatives.
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