The Annals of Statistics

A Simple Solution to a Nonparametric Maximum Likelihood Estimation Problem

Gilbert G. Walter and Julius R. Blum

Full-text: Open access

Abstract

Three approaches to a nonparametric maximum likelihood problem are considered. One, based on the method of "sieves", is shown to include the other two. The sieve considered is a double exponential convolution sieve. A closed form solution is given for certain values of the sieve parameter.

Article information

Source
Ann. Statist., Volume 12, Number 1 (1984), 372-379.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176346415

Digital Object Identifier
doi:10.1214/aos/1176346415

Mathematical Reviews number (MathSciNet)
MR733522

Zentralblatt MATH identifier
0591.62032

JSTOR
links.jstor.org

Subjects
Primary: 62605

Keywords
Sieves Sobolev space maximum likelihood nonparametric estimation

Citation

Walter, Gilbert G.; Blum, Julius R. A Simple Solution to a Nonparametric Maximum Likelihood Estimation Problem. Ann. Statist. 12 (1984), no. 1, 372--379. doi:10.1214/aos/1176346415. https://projecteuclid.org/euclid.aos/1176346415


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