Multivariate Autoregressive Time Series Using Schweppe Weighted Wilcoxon Estimates

DOI10.1007/978-3-319-39065-9_13zbMath1366.62172OpenAlexW21495671MaRDI QIDQ5280271

Jaime Burgos, Jeffrey T. Terpstra

Publication date: 20 July 2017

Published in: Robust Rank-Based and Nonparametric Methods (Search for Journal in Brave)

Full work available at URL: https://scholarworks.wmich.edu/dissertations/239

zbMATH Keywords

outliersasymptotic normalityMonte Carlo studyU-statisticsvector autoregressiveWilcoxon estimatesmultivariate autoregressive time seriesSchweppe

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Nonparametric robustness (62G35)

Uses Software

• R
• itsmr

Cites Work

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• Multivariate functional least squares
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• On U-statistics and v. mise? statistics for weakly dependent processes
• Asymptotic normality ofr-estimates in the linear model
• Robust multiple time series modelling
• Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals
• Introduction to Time Series and Forecasting
• Theory & Methods: Weighted Wilcoxon Estimates for Autoregression
• High-Breakdown Rank Regression
• Robust Nonparametric Statistical Methods
• Generalized rank estimates for an autoregressive time series: A \(U\)-statistic approach

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