Time-frequency clustering and discriminant analysis.
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Publication:1423186
DOI10.1016/S0167-7152(03)00095-6zbMath1116.62364MaRDI QIDQ1423186
Publication date: 14 February 2004
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics (62P99)
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Cites Work
- Unnamed Item
- AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
- Fitting time series models to nonstationary processes
- Discriminant analysis for locally stationary processes
- On the Kullback-Leibler information divergence of locally stationary processes
- Discrimination and Clustering for Multivariate Time Series
- Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance
- Automatic Statistical Analysis of Bivariate Nonstationary Time Series
- Time-Dependent Spectral Analysis of Nonstationary Time Series