New independent component analysis tools for time series

DOI10.1016/J.SPL.2015.04.033zbMath1396.62214OpenAlexW608794380WikidataQ109772925 ScholiaQ109772925MaRDI QIDQ894577

Hannu Oja, Klaus Nordhausen, Markus Matilainen

Publication date: 1 December 2015

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2015.04.033

zbMATH Keywords

JADEstochastic volatilitymultivariate statisticsGARCHFOBISOBI

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (7)

Stationary subspace analysis based on second-order statistics ⋮ Extracting Conditionally Heteroskedastic Components using Independent Component Analysis ⋮ Blind source separation for compositional time series ⋮ Sliced average variance estimation for multivariate time series ⋮ Separation of Uncorrelated Stationary time series using Autocovariance Matrices ⋮ Independent component analysis for multivariate functional data ⋮ On the usage of joint diagonalization in multivariate statistics

Uses Software

• R
• RMetrics
• fGarch
• JADE
• GHICA

Cites Work

• Unnamed Item
• Fourth moments and independent component analysis
• Deflation-based separation of uncorrelated stationary time series
• Statistical properties of a blind source separation estimator for stationary time series
• On the Ghurye-Olkin-Zinger theorem
• Portfolio value at risk based on independent component analysis
• Separation of Uncorrelated Stationary time series using Autocovariance Matrices
• Dynamic Orthogonal Components for Multivariate Time Series
• On Invariant Coordinate System (ICS) Functionals
• Measures of multivariate skewness and kurtosis with applications

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