Weighted least squares estimates in partly linear regression models
AbstractThis paper constructs root-n consistent weighted least squares estimates with random weights of the finite-dimensional parameter in the partly linear regression model with heteroscedastic errors. These new estimates have smaller asymptotic dispersion than the least squares type estimates previously constructed in these models.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 27 (1996)
Issue (Month): 3 (April)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
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