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Statistics of Random Processes II: Applications Rev and Expande Edition
Contributor(s): Liptser, Robert S. (Author), Aries, A. B. (Translator), Shiryaev, Albert N. (Author)
ISBN: 3540639284     ISBN-13: 9783540639282
Publisher: Springer
OUR PRICE:   $151.99  
Product Type: Hardcover - Other Formats
Published: November 2000
Qty:
Annotation: The subject of these two volumes is non-linear filtering (prediction and smoothing) theory and its application to the problem of optimal estimation, control with incomplete data, information theory, and sequential testing of hypothesis. The book is not only addressed to mathematicians but should also serve the interests of other scientists who apply probabilistic and statistical methods in their work. The theory of martingales presented in the book has an independent interest in connection with problems from financial mathematics.
In the second edition, the authors have made numerous corrections, updating every chapter, adding two new subsections devoted to the Kalman filter under wrong initial conditions, as well as a new chapter devoted to asymptotically optimal filtering under diffusion approximation. Moreover, in each chapter a comment is added about the progress of recent years.
Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
Dewey: 519.23
LCCN: 00041918
Series: Stochastic Modelling and Applied Probability
Physical Information: 1.14" H x 6.5" W x 9.49" (1.62 lbs) 402 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
At the end of 1960s and the beginning of 1970s, when the Russian version of this book was written, the 'general theory of random processes' did not operate widely with such notions as semimartingale, stochastic integral with respect to semimartingale, the Ito formula for semimartingales, etc. At that time in stochastic calculus (theory of martingales), the main object was the square integrable martingale. In a short time, this theory was applied to such areas as nonlinear filtering, optimal stochastic control, statistics for diffusion- type processes. In the first edition of these volumes, the stochastic calculus, based on square integrable martingale theory, was presented in detail with the proof of the Doob-Meyer decomposition for submartingales and the description of a structure for stochastic integrals. In the first volume ('General Theory') these results were used for a presentation of further important facts such as the Girsanov theorem and its generalizations, theorems on the innovation pro- cesses, structure of the densities (Radon-Nikodym derivatives) for absolutely continuous measures being distributions of diffusion and ItO-type processes, and existence theorems for weak and strong solutions of stochastic differential equations. All the results and facts mentioned above have played a key role in the derivation of 'general equations' for nonlinear filtering, prediction, and smoothing of random processes.