Most currently employed methods that are used in various fields of data analysis, such as signal processing and time series analysis, are based on rather simplistic assumptions about the linearity and stationarity of the underlying processes, and are hence suboptimal in many situations. The chapters in this book introduce modern methods that have been developed in many fields of statistics, engineering, environmental science or finance, to address these shortcomings. The authors present state-of-the-art statistical methods, and discuss their applications in real-world situations. The chapters, taken together, provide a coherent and unique account of this active and important area, that will appeal to graduate students and researchers in academia, industry and laboratories.
"synopsis" may belong to another edition of this title.
'... is a useful progress report for anyone seeking to go beyond the basics, and a good addition to the comparatively small literature on non-stationary and nonlinear processes.' Carl Wunsch, EOS
'I have no doubt many readers will find this volume useful.' T. Subba Rao, Publication of the International Statistical Institute
'... will certainly be welcomed by those wishing to understand and apply the latest techniques in this area.' Alex M. Andrew, Robotica
Most currently employed methods used in various fields of data analysis are based on rather simplistic assumptions and are hence suboptimal in many situations. This book introduces modern methods that have been developed to address these shortcomings. It is a coherent and unique account of this active and important area.
"About this title" may belong to another edition of this title.
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Hardcover. Condition: Near Fine. 2000, First Edition, Near Fine/no dj, small quarto, 471pp., pictorial glossy boards hardcover, binding tight, owner's inked name on endpaper o/w unmarked. Seller Inventory # 16916
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