A general result on the uniform in bandwidth consistency of kernel-type function estimators
We develop a general theorem to prove the uniform in bandwidth consistency of kernel-type function estimators. This method unifies the approaches in some other recent papers. We show how to apply our results to kernel distribution function estimators and the smoothed empirical process. The results are applicable to establish strong uniform consistency of data-driven bandwidth kernel-type function estimators. Copyright Sociedad de Estadística e Investigación Operativa 2011
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Volume (Year): 20 (2011)
Issue (Month): 1 (May)
Pages: 72-94
| Handle: | RePEc:spr:testjl:v:20:y:2011:i:1:p:72-94 |
| Contact details of provider: | Web page: http://www.springer.com Web page: http://www.seio.es/
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| Order Information: | Web: http://www.springer.com/statistics/journal/11749/PS2 |
References listed on IDEAS
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- D. Boos, 1986. "Rates of convergence for the distance between distribution function estimators," Metrika- International Journal for Theoretical and Applied Statistics, Springer, vol. 33(1), pages 197-202, December.
- Jan W. H. Swanepoel & Francois C. Van Graan, 2005. "A New Kernel Distribution Function Estimator Based on a Non-parametric Transformation of the Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(4), pages 551-562.
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