The influence functions for the least trimmed squares and the least trimmed absolute deviations estimators

Mara Tableman

Statistics & Probability Letters, 1994, vol. 19, issue 4, 329-337

Abstract: The influence functions for Rousseeuw's (1987) least trimmed squares (LTS) estimator and for Tableman's (1994) least trimmed absolute deviations (LTAD) estimator are derived in the univariate case. The half-sample estimators which possess, by construction, the 50% breakdown point property satisfy three of the four robustness criteria defined by Hampel (1986). They have bounded influence functions, finite gross-error sensitivity, and finite rejection point. However, they have infinite local-shift sensitivity. Hence, these estimates can be highly sensitive to small perturbations in the data. Small shifts in centrally located data (inliers) can cause their values to change by relatively large (though bounded) amounts.

Keywords: Breakdown; point; gross-error; sensitivity; influence; function; least; trimmed; absolute; deviations; least; trimmed; squares; local-shift; sensitivity; rejection; point; robust (search for similar items in EconPapers)
Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(94)90186-4
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:stapro:v:19:y:1994:i:4:p:329-337

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().