Discussion of the Paper “Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models” by Johansen & Nielsen

DOI10.1111/sjos.12214zbMath1419.62246OpenAlexW2513279456MaRDI QIDQ2815582

Elvezio Ronchetti

Publication date: 29 June 2016

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/sjos.12214

zbMATH Keywords

false discovery rateoutlier detectionmartingale inequalitiesnonstationary regressorsHuber-skip estimatorsone-step \(M\)-estimatorssmooth outlier rejection

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Nonparametric robustness (62G35) Non-Markovian processes: hypothesis testing (62M07)

Cites Work

• A journey in single steps: robust one-step \(M\)-estimation in linear regression
• The Breakdown Points of the Mean Combined with Some Rejection Rules
• Robust Estimation of a Location Parameter
• Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models

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