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Sensitivity analysis in linear models

By Liu Shuangzhe, Ma Tiefeng and Liu Yonghui


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

Topics: elliptical distribution, least squares, maximum likelihood, mixed estimation, sensitivity matrix, Mathematics, QA1-939
Publisher: De Gruyter Open
Year: 2016
DOI identifier: 10.1515/spma-2016-0021
OAI identifier: oai:doaj.org/article:5f3996975f1c49e589e04b1da8f249e2
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