Sieves for Nonparametric Estimation of Densities and Regressions.
Abstract
This report is about the use of least-squares for nonparametric regression and the use of maximum likelihood for nonparametric density estimation. Typically, these classical techniques fail when applied to infinite dimensional problems. Grenander's method of sieves is a method for modifying classical estimators to make them appropriate for nonclassical problems. Examples are given here of the application of this method to the problems of regression and density estimation. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1981
- Accession Number
- ADA096751
Entities
People
- Stuart Geman
Organizations
- Brown University