Estimating covariance matrices using estimating functions in nonparametric and semiparametric regression

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.

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Year of publication:	1997
Authors:	Carroll, Raymond J. ; Iturria, Stephen J. ; Gutierrez, Roberto G.
Institutions:	Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät
Subject:	Nonparametric regression \| Estimating Equations \| Kernel regression \| Plug-in Semiparametrics \| Smoothing

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Extent:	application/pdf
Series:	SFB 373 Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 1997,14
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010956344