Isotonic estimation for grouped data

A non-parametric estimator of a non-increasing density is found in a class of piecewise linear functions when the data consist only of counts. An EM-Algorithm for computing the estimator is developed, and the iterates in the algorithm are shown to converge to the maximum likelihood estimator. Potential applications to distance sampling models are described and illustrated with a numerical example.

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Year of publication:	1999
Authors:	Woodroofe, Michael ; Zhang, Rong
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 45.1999, 1, p. 41-47
Publisher:	Elsevier
Keywords:	Counts Distance sampling EM-Algorithm Maximum likelihood estimation

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005223485