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Forecast Time Series

 

Caterpillar SSA - time series analysis and forecast

 

Books

 

Singular Spectrum Analysis for Time Series The book "Singular Spectrum Analysis for Time Series" (2013, in English) is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.

 

Analysis of Time Series Structure: SSA and Related Techniques The book "Analysis of time series structure: SSA and related techniques" (2001, in English) provides a careful, lucid description of the 'Caterpillar'-SSA general theory and methodology. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers you the opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications. All examples of the book are obtained with the help of the CaterpillarSSA v3.10 software.

 

Principal Components of Time Series: the Caterpillar Method The book "Principal Components of Time Series: the Caterpillar Method" (1997, in Russian) forms the basis of the Russian part of this site. The collection of papers is devoted to the unified theme: methodology (with many examples), theoretical ground and practicality of the method.

 

Special Issue "Theory and Practice in Singular Spectrum Analysis of Time Series"
of the journal Statistics and Its Interface, 2010, v. 3, No. 3:

(draft versions are published in Arxiv)
  • A.Korobeynikov
    Computation- and Space-Efficient Implementation of SSA. P.357-368
    arXiv:0911.4498
  • V.Nekrutkin
    Perturbation expansions of signal subspaces for long signals. P.297-319
    arXiv:1001.1051
  • K.Usevich
    On signal and extraneous roots in Singular Spectrum Analysis. P.281-295
    arXiv:1006.3436
  • N.Golyandina
    On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods. P.259-279
    arXiv:1005.4374

 
 
 
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Analysis Time Series