Proving consistency of non-standard kernel estimators

We develop general methods based upon empirical process techniques to prove uniform in bandwidth consistency of a class of non-standard kernel-type function estimators. Examples include projection pursuit regression and conditional distribution estimation. Our results are especially useful to establ...

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Veröffentlicht in:	Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems 2012-07, Vol.15 (2), p.151-176
1. Verfasser:	Mason, David M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Mathematics Mathematics and Statistics Probability Theory and Stochastic Processes Statistical Theory and Methods
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	We develop general methods based upon empirical process techniques to prove uniform in bandwidth consistency of a class of non-standard kernel-type function estimators. Examples include projection pursuit regression and conditional distribution estimation. Our results are especially useful to establish uniform consistency of data-driven bandwidth kernel-type function estimators.
ISSN:	1387-0874 1572-9311
DOI:	10.1007/s11203-012-9068-4