USE OF “CATERPILLAR” – SSA METHOD FOR ANALYSIS AND FORECASTING OF INDUSTRIAL AND ECONOMIC INDICATORS
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Alexandrov Th., Golyandina N. Automatic extraction and forecast of time series cyclic components within the framework of SSA. In: Proceedings of the 5th St.Petersburg Workshop on Simulation, June 26-July 2, 2005, St. Petersburg State University, St. Petersburg, pp. 45-50.
Antoniou V.V. et al. Principal Component Analysis of Network Traffic: the “Caterpillar” - SSA Approach, VIII Int. Workshop on “Advanced Computing and Analysis Techniques in Physics Research”, ACAT‟ 2002, 24-28 June 2002, Moscow, Russia, Book of abstracts, p. 176.
Cadzow J.A. Signal Enhancement - A Composite Property Mapping Algorithm. IEEE Transactions on Acoustics, Speech and Signal Processing, 1988. V. 36, pp. 49-62.
Danilov D., Zhigljavsky A. eds. Principal Components of Time Series: "Caterpillar" Method. St. Petersburg University, 1997. http://www.gistatgroup.com/gus/
Ghil M. et al.: Climatic time seriers analysis: Reviews of Geophysics, 40, 1 / Month 2002 pages 1-1–1-41
Golyandina N., Nekrutkin V., Zhigljavsky A. Analysis of Time Series Structure: SSA and Related Techniques. London: Chapman and Hall, 2001.
Golyandina N., Usevich K., Florinsky I. Filtering of Digital Terrain Models by two-dimensional Singular Spectrum Analysis. International Journal of Ecology & Development, 2007. Vol. 8, No. F07, P.81-94.
Golyandina N.E., Nekrutkin V.V., and Stepanov D.V. Variants of the “Caterpillar”-SSA method for analysis of multidimensional time series. http://www.gistatgroup.com/cat/
Golyandina N., Osipov E. The "Caterpillar"- SSA method for analysis of time series with missing values Journal of Statistical Planning and Inference, Volume 137, Issue 8, 1 August 2007. pp. 2642-2653.
Jolliffe I.T. Principal Component Analysis. Springer-Verlag, 1986.
Keppenne C., Lall U. Complex singular spectrum analysis and multivariate adaptive regression splines applied to forecasting the southern oscillation // Exp.LongLead Forcst. Bull. 1996. http://www.cpc.ncep.noaa.gov/products/predictions/experimental/bulletin/Mar96/article13.html
LR Centrālā statistiskas pārvalde. Datubāzes. http://www.csb.gov.lv
Preizendorfer R.W. Principal Component Analysis in Meteorology and Oceanography. Elsevier, 1988.
Schoellhamer D.H. Singular spectrum analysis for time series with missing data. Geophysical Research Letters, V. 28, no. 16, 2001. pp. 3187-3190.
Stepanov D., Golyandina N. SSA-based approaches to analysis and forecast of multidimensional time series. In: Proceedings of the 5th St.Petersburg Workshop on Simulation, June 26-July 2, 2005, St. Petersburg State University, St. Petersburg, pp. 293-298.
Vautard R., Yiou P., Ghil M. Singular Spectrum Analysis: A Toolkit for Short, Noisy Chaotic Signals, Physica D. 1992. V. 58, pp. 95-126.
DOI: https://doi.org/10.17770/etr2009vol2.1030
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