This book gives an overview of singular spectrum analysis (SSA). SSA is
a technique of time series analysis and forecasting combining elements
of classical time series analysis, multivariate statistics, multivariate
geometry, dynamical systems and signal processing. SSA is multi-purpose
and naturally combines both model-free and parametric techniques, which
makes it a very special and attractive methodology for solving a wide
range of problems arising in diverse areas. Rapidly increasing number of
novel applications of SSA is a consequence of the new fundamental
research on SSA and the recent progress in computing and software
engineering which made it possible to use SSA for very complicated tasks
that were unthinkable twenty years ago. In this book, the methodology of
SSA is concisely but at the same time comprehensively explained by two
prominent statisticians with huge experience in SSA. The book offers a
valuable resource for a very wide readership, including professional
statisticians, specialists in signal and image processing, as well as
specialists in numerous applied disciplines interested in using
statistical methods for time series analysis, forecasting, signal and
image processing. The second edition of the book contains many updates
and some new material including a thorough discussion on the place of
SSA among other methods and new sections on multivariate and
multidimensional extensions of SSA.
