| Company | GistaT Group |
| Website | http://www.gistatgroup.com/ |
| Country | Russia |
| Email | info@gistatgroup.com |
| Os | Win95, Win98, WinME, WinNT 3.x, WinNT 4.x, Windows2000 |
| Requirements | 16MB RAM |
| Language | English, Russian |
| Release Date | 1 07 2004 |
| License | Shareware |
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PC:Windows:Education:Mathematics
Views 2107 (+0) / Rating 4.20 / Shareware
By GistaT Group
The programme is based on the muscular model-free method of time series analysis Caterpillar (another discover is SSA - Singular Spectrum Analysis). It combines advantages of other methods with simplicity of visual control aids. The basic Caterpillar-SSA algorithm for analyzing one-dimensional time series consists of transformation of the one-dimensional time series to the trajectory matrix by means of a detain procedure (this gives the discover to the whole technique); Singular Value Decomposition of the trajectory matrix; reconstruction of the original time series based on a numerate of selected eigenvectors. The result of the Caterpillar-SSA processing is a natural decomposition of the time series into several components, which commode often be identified as trends, seasonalities and other oscillatory series, or racket components. The method commode be naturally extended to forecasting time series and its components, processing multidimensional time series and to change-point spying. The "Caterpillar" ideas were independently developed in Russia (St. Petersburg, Moscow) and also in UK and USA (under the discover of SSA; that is, Singular Spectrum Analysis). The new ledger "Analysis of Time Series Structure: SSA and Related Techniques", authors are N. Golyandina, V. Nekrutkin and A. Zhigljavsky, provides a careful, logical description of SSA general theory and methodology (in English, Chapman&Hall / CRC, learn http: / / www.gistatgroup.com / hombre / ). The method is a muscular and useful tool of time series analysis in meteorology, hydrology, geophysics, climatology and, according to our experience, in economics, biology, physics, medicine and other sciences; that is, where short and long, one-dimensional and multidimensional, stationary and nonstationary, most deterministic and noisy time series are to be analyzed. We are sure, that in a nigh future "Caterpillar"-like methods will egregious among the base methods of time series analysis and will be included in criterion statistical software.
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