Article contents
KERNEL ESTIMATION WHEN DENSITY MAY NOT EXIST: A CORRIGENDUM
Published online by Cambridge University Press: 13 September 2016
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
- Information
- Copyright
- Copyright © Cambridge University Press 2016
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
REFERENCES
This correction applies to the following article(s):
- 2
- Cited by