Estimating covariance matrices using estimating functions in nonparametric and semiparametric regression

Raymond J. Carroll, Stephen J. Iturria and Roberto G. Gutierrez

No 1997,14, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: We use ideas from estimating function theory to derive new, simply computed consistent covariance matrix estimates in nonparametric regression and in a class of semiparametric problems. Unlike other estimates in the literature, ours do not require auxiliary or additional nonparametric regressions.

Keywords: Nonparametric regression; Estimating Equations; Kernel regression; Plug-in Semiparametrics; Smoothing (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:199714

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