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Stochastic Processes: Inference Theory 2000 Edition
Contributor(s): Rao, Malempati M. (Author)
ISBN: 0792363248     ISBN-13: 9780792363248
Publisher: Springer
OUR PRICE:   $208.99  
Product Type: Hardcover - Other Formats
Published: May 2000
Qty:
Annotation: This book presents a complete mathematical treatment of classical inference theory (Neyman-Pearson, Fisher, and Wald) from the point of using it in stochastic processes, including some generalizations. It includes detailed analysis of likelihood ratios for both Gaussian and several other classes (infinitely divisible, jump Markov, diffusion and additive). Both linear and nonlinear filtering (also for general nonquadratic criteria) are treated. The corresponding Kalman-Bucy filters for continuous parameter processes are presented. Consistency and limit distributions of estimations of biospectral densities of harmonizable processes are given. Audience: Researchers and graduate students working in mathematics, statistics, and systems and communication engineering.
Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
Dewey: 519.23
LCCN: 00039096
Series: Mathematics and Its Applications
Physical Information: 1.44" H x 6.14" W x 9.21" (2.43 lbs) 645 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
The material accumulated and presented in this volume can be ex- plained easily. At the start of my graduate studies in the early 1950s, I Grenander's (1950) thesis, and was much attracted to the came across entire subject considered there. I then began preparing for the neces- sary mathematics to appreciate and possibly make some contributions to the area. Thus after a decade of learning and some publications on the way, I wanted to write a modest monograph complementing Grenander's fundamental memoir. So I took a sabbatical leave from my teaching position at the Carnegie-Mellon University, encouraged by an Air Force Grant for the purpose, and followed by a couple of years more learning opportunity at the Institute for Advanced Study to complete the project. As I progressed, the plan grew larger needing a substantial background material which was made into an independent initial volume in (1979). In its preface I said: "My intension was to present the following material as the first part of a book treating the In- ference Theory of stochastic processes, but the latter account has now receded to a distant future," namely for two more decades Meanwhile, a much enlarged second edition of that early work has appeared (1995), and now I am able to present the main part of the original plan.