Semiparametric models: a generalized self-consistency approach

Author: Tsodikov, A.

Source: Journal of the Royal Statistical Society: Series B (Statistical Methodology), Volume 65, Number 3, August 2003 , pp. 759-774(16)

Publisher: Wiley-Blackwell

Buy & download fulltext article:

OR

Price: $48.00 plus tax (Refund Policy)

Abstract:

Summary.

In semiparametric models, the dimension d of the maximum likelihood problem is potentially unlimited. Conventional estimation methods generally behave like O(d3). A new O(d) estimation procedure is proposed for a large class of semiparametric models. Potentially unlimited dimension is handled in a numerically efficient way through a Nelson–Aalen-like estimator. Discussion of the new method is put in the context of recently developed minorization–maximization algorithms based on surrogate objective functions. The procedure for semiparametric models is used to demonstrate three methods to construct a surrogate objective function: using the difference of two concave functions, the EM way and the new quasi-EM (QEM) approach. The QEM approach is based on a generalization of the EM-like construction of the surrogate objective function so it does not depend on the missing data representation of the model. Like the EM algorithm, the QEM method has a dual interpretation, a result of merging the idea of surrogate maximization with the idea of imputation and self-consistency. The new approach is compared with other possible approaches by using simulations and analysis of real data. The proportional odds model is used as an example throughout the paper.

Keywords: EM algorithm; Frailty; Nonparametric maximum likelihood estimation; Profile likelihood; Semiparametric models

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/1467-9868.00414

Affiliations: University of Utah, Salt Lake City, USA

Publication date: August 1, 2003

Related content

Tools

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page