Sensitivity analysis in linear models

Shuangzhe LIU, Tiefeng Ma, Yonghui Liu

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

4 Citations (Scopus)
43 Downloads (Pure)


In this work, we consider the general linear model or its variants with the ordinary least squares, generalised least squares or restricted least squares estimators of the regression coefficients and variance. We propose a newly unified set of definitions for local sensitivity for both situations, one for the estimators of the regression coefficients, and the other for the estimators of the variance. Based on these definitions, we present the estimators' sensitivity results. We include brief remarks on possible links of these definitions and sensitivity results to local influence and other existing results.

Original languageEnglish
Title of host publicationSpecial Matrices Topical Issue on Proceedings of the 24th International Workshop on Matrices and Statistics
EditorsJeffrey J Hunter, Simo Puntanen, Dietrich van Rosen
Place of PublicationWarsaw Poland
PublisherWalter de Gruyter
Number of pages8
Publication statusPublished - 2016
Event24th Internatiopnal Workshop on Matrices and Statistics - Haikou, Haikou, China
Duration: 25 May 201528 May 2015 (Conference website)

Publication series

NameSpecial Matrices
PublisherDe Gruyter Open Ltd.
ISSN (Print)2300-7451


Conference24th Internatiopnal Workshop on Matrices and Statistics
Abbreviated titleIWMS
Internet address


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