Some heuristics of kernel based estimators of ratio functions
| Autor: | Prakash Patil, James Stephen Marron, M. T. Wells |
|---|---|
| Rok vydání: | 1994 |
| Předmět: |
Statistics and Probability
Mean integrated squared error Variable kernel density estimation Entire function Statistics Nonparametric statistics Estimator Applied mathematics Statistics Probability and Uncertainty Heuristics Martingale (probability theory) Multivariate kernel density estimation Mathematics |
| Zdroj: | Journal of Nonparametric Statistics. 4:203-209 |
| ISSN: | 1029-0311 1048-5252 |
| DOI: | 10.1080/10485259408832611 |
| Popis: | Ratio functions for which nonparametric estimators have been considered include the hazard rate and density under random censoring. One estimation method involves individual estimates of the numerator and denominator. An alternative targets the entire function not the separate pieces. The two estimators are not comparable in terms of Mean Integrated Squared Error. However, the second type is seen to be more natural because it admits an elegant and useful martingale representation, and also is pictorially more attractive. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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