A variance shift model for detection of outliers in the linear measurement error model
type: Item
instance of: scholarly article
title: A variance shift model for detection of outliers in the linear measurement error model
zbMATH Open document ID: 1472.62070
DOI: 10.1155/2014/396875
author: Xianqiang Yang
published in: Abstract and Applied Analysis
publication date: 2019-02-14T00:00:00Z
review text: Summary: We present a variance shift model for a linear measurement error model using the corrected likelihood of \textit{T. Nakamura} [Biometrika 77, No. 1, 127--137 (1990; Zbl 0691.62066)]. This model assumes that a single outlier arises from an observation with inflated variance. The corrected likelihood ratio and the score test statistics are proposed to determine whether the \(i\)th observation has an inflated variance. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics and a simulation study has been used to show the performance of proposed tests. Finally, a real data example is given for illustration.
Mathematics Subject Classification ID: 62G32
Mathematics Subject Classification ID: 62J02
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 60F10
zbMATH DE Number: 7022311
zbMATH Keywords: detection of outliers
Wikidata QID: Q59037320
describes a project that uses: alr3
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/396875
OpenAlex ID: W2091230523
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description: scientific article; zbMATH DE number 7022311