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Computing least trimmed squares regression with the forward search

Atkinson, Anthony C. and Cheng, T.-C. (1999) Computing least trimmed squares regression with the forward search. Statistics and Computing, 9 (4). pp. 251-263. ISSN 0960-3174

Full text not available from this repository.
Identification Number: 10.1023/A:1008942604045

Abstract

Least trimmed squares (LTS) provides a parametric family of high breakdown estimators in regression with better asymptotic properties than least median of squares (LMS) estimators. We adapt the forward search algorithm of Atkinson (1994) to LTS and provide methods for determining the amount of data to be trimmed. We examine the efficiency of different trimming proportions by simulation and demonstrate the increasing efficiency of parameter estimation as larger proportions of data are fitted using the LTS criterion. Some standard data examples are analysed. One shows that LTS provides more stable solutions than LMS.

Item Type: Article
Official URL: http://www.springerlink.com
Additional Information: © 1999 Statistics and Computing
Subjects: Q Science > QA Mathematics
Sets: Departments > Statistics
Date Deposited: 13 Feb 2010 12:28
Last Modified: 19 Apr 2016 09:23
URI: http://eprints.lse.ac.uk/id/eprint/7611

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