The developers of the SSA-MTM Toolkit are researchers attempting to make some useful time-series analysis methods more accessible to the scientific community. Although we use the tools ourselves and have made every effort to ensure their accuracy, we can not make any guarantees. We provide the Toolkit to you for free, but it is copyrighted. In return, you--the user--assume full responsibility for use of the software. The SSA-MTM Toolkit and this Guide come without any warranties (implied or expressed) and are not guaranteed to work for you or on your computer. Specifically, the University of California, Los Angeles, Department of Atmospheric Sciences; U.S. Geological Survey; Commissariat à l'Énergie Atomique; and the various individuals involved in development and maintenance of the SSA-MTM Toolkit are not responsible for any damage that may result from correct or incorrect use of this software.

This guide may be reproduced and distributed freely, provided that this page is preserved on all copies and remains unaltered.

If you feel that your research has benefited from the use of the SSA-MTM Toolkit, you can repay us by citing our articles:

  • Ghil M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, M. E. Mann, A. Robertson, A. Saunders, Y. Tian, F. Varadi, and P. Yiou, 2002: Advanced spectral methods for climatic time series, Rev. Geophys.,40(1), pp. 3.1-3.41.
  • Dettinger, M.D., Ghil, M., Strong, C.M., Weibel, W., and Yiou, P., 1995: Software expedites singular-spectrum analysis of noisy time series, Eos, Trans. American Geophysical Union, v. 76(2), p. 12, 14, 21.

We also appreciate your references to the original articles that motivated and made the toolkit possible (see the reference list), and especially to

  • Allen, M.R., and Smith, L.A., 1996: Monte Carlo SSA: detecting oscillations in the presence of coloured noise. J. Climate, 9, 3373.
  • Allen M. R., Robertson A. W. (1996) Distinguishing modulated oscillations from coloured noise in multivariate datasets. Clim. Dyn. 12, 775-784
  • Mann, M.E. and Lees, J.M., 1996: Robust estimation of background noise and signal detection in climatic time series, Clim. Change, 33, 409-445.Vautard, R., Yiou, P., and Ghil, M., 1992: Singular-spectrum analysis: A toolkit for short, noisy chaotic signals, Physica D, 58, 95-126.