Fourier and Hermite series estimates of regression functions

Annals of the Institute of Statistical Mathematics

Volumn 37, Issue 1, 1985, Pages 443-454

  Greblicki, Wlodzimier ^a,b   Pawlak, Miroslaw ^a,b  

^a WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

Fourier series; Hermite series; nonparameteric estimate; Regression function

Indexed keywords

EID: 51249178643     PISSN: 00203157     EISSN: 15729052     Source Type: Journal    
DOI: 10.1007/BF02481112     Document Type: Article

References (22)

1. Conditions nécessaires et suffisantes de convergence pour une class d'estimateurs de la densité
2. Estimation non paramétrique de la regression: revue bibliographique
3. A general method for density estimation
4. Consistency conditions for probability estimators and integrals for density estimators
5. Distribution-free pointwise consistency of kernel regression estimates
6. Hermite series estimate of a probability density and its derivatives
7. Probability inequalities for sums of bounded random variables
8. The estimation of probability densities and cumulatives by Fourier series methods
9. Distribution-free consistency of nonparametric kernel regression estimate and classification
10. On estimating regression
11. Estimation of probability density by an orthogonal series
12. Optimal rates of convergence for non-parametric estimators
13. On multivariate density estimates based on orthogonal expansions
14. Optimal convergence properties of varaible knot, kernel and orthogonal series methods for density estimation
15. Properties of Hermite series estimation of probability density
16. Smooth regression analysis