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

Ori Davidov and George Iliopoulos

Computational Statistics & Data Analysis, 2010, vol. 54, issue 3, 620-624

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.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00405-2
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:54:y:2010:i:3:p:620-624

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().