Extent to which least-squares cross-validation minimises integrated square error in nonparametric density estimation
- 1 April 1987
- journal article
- research article
- Published by Springer Nature in Probability Theory and Related Fields
- Vol. 74 (4), 567-581
- https://doi.org/10.1007/bf00363516
Abstract
No abstract availableKeywords
This publication has 16 references indexed in Scilit:
- An Asymptotically Efficient Solution to the Bandwidth Problem of Kernel Density EstimationThe Annals of Statistics, 1985
- Bandwidth Choice for Nonparametric RegressionThe Annals of Statistics, 1984
- An alternative method of cross-validation for the smoothing of density estimatesBiometrika, 1984
- Cross-validation in nonparametric estimation of probabilities and probability densitiesBiometrika, 1984
- Central limit theorem for integrated square error of multivariate nonparametric density estimatorsJournal of Multivariate Analysis, 1984
- Large Sample Optimality of Least Squares Cross-Validation in Density EstimationThe Annals of Statistics, 1983
- Consistent Cross-Validated Density EstimationThe Annals of Statistics, 1983
- Limit theorems for stochastic measures of the accuracy of density estimatorsStochastic Processes and their Applications, 1982
- On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density FunctionsIEEE Transactions on Computers, 1976
- On Some Global Measures of the Deviations of Density Function EstimatesThe Annals of Statistics, 1973