A note on an iterative algorithm for nonparametric estimation in biased sampling models

Ori Davidov, George Iliopoulos

Research output: Contribution to journalArticlepeer-review

Abstract

A simple iterative estimation procedure for computing the nonparametric maximum likelihood estimator (NPMLE) in biased sampling models is discussed and studied in detail. A proof of convergence is provided. Numerical experiments show that the algorithm is significantly faster in terms of CPU time compared with the standard procedure.

Original languageEnglish
Pages (from-to)620-624
Number of pages5
JournalComputational Statistics and Data Analysis
Volume54
Issue number3
DOIs
StatePublished - 1 Mar 2010

Bibliographical note

Funding Information:
This research was supported by the Israel Science Foundation grant No. 1049/06.

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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