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KERNEL ESTIMATION WHEN DENSITY MAY NOT EXIST: A CORRIGENDUM

Published online by Cambridge University Press:  13 September 2016

Victoria Zinde-Walsh*
Affiliation:
McGill University and CIREQ
*
*Address correspondence to Victoria Zinde-Walsh, Department of Economics, McGill University, 855 Sherbrooke Street West, Montreal, QC H3A 2T7, Canada; e-mail: [email protected].

Abstract

The paper “Kernel estimation when density may not exist” (Zinde-Walsh, 2008) considered density as a generalized function given by a functional on a space of smooth functions; this made it possible to establish the limit properties of the kernel estimator without assuming the existence of the density function. This note corrects an error in that paper in the derivation of the variance of the kernel estimator. The corrected result is that in the space of generalized functions the parametric rate of convergence of the kernel density estimator to the limit Gaussian process is achievable.

Type
CORRIGENDUM
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

The support of the Social Sciences and Humanities Research Council of Canada (SSHRC) and the Fonds québecois de la recherche sur la société et la culture (FRQSC) is gratefully acknowledged. I thank John Galbraith, Yanqin Fan, the Editor and referees for helpful advice.

References

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