On Rates of Convergence in the L2 Norm of Nonparametric Probability Density Estimates.
Abstract
For estimation of a probability density function f by an empirical probability density function f sub n based on a sample of size n from f, a useful measure of distance is the L2-norm. Considerable study of the rate of mean square convergence of abs. val. (f sub n-f) to 0 has taken place. This paper investigates the rate of almost sure convergence of abs. val. (f sub n-f) to 0. Application to certain estimation problems in nonparametric inference is discussed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1979
- Accession Number
- ADA072134
Entities
People
- K. F. Cheng
- Robert Serfling
Organizations
- Florida State University