Statistics of Random Processes II Applications

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 required mathematical background is presented in the first...

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Bibliographic Details
Main Authors: Liptser, Robert S., Shiryaev, Albert N. (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2001, 2001
Edition:2nd ed. 2001
Series:Stochastic Modelling and Applied Probability
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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245 0 0 |a Statistics of Random Processes II  |h Elektronische Ressource  |b Applications  |c by Robert S. Liptser, Albert N. Shiryaev 
250 |a 2nd ed. 2001 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 2001, 2001 
300 |a XV, 402 p  |b online resource 
505 0 |a 11. Conditionally Gaussian Processes -- 12. Optimal Nonlinear Filtering: Interpolation and Extrapolation of Components of Conditionally Gaussian Processes -- 13. Conditionally Gaussian Sequences: Filtering and Related Problems -- 14. Application of Filtering Equations to Problems of Statistics of Random Sequences -- 15. Linear Estimation of Random Processes -- 16. Application of Optimal Nonlinear Filtering Equations to some Problems in Control Theory and Estimation Theory -- 17. Parameter Estimation and Testing of Statistical Hypotheses for Diffusion-Type Processes -- 18. Random Point Processes: Stieltjes Stochastic Integrals -- 19. The Structure of Local Martingales, Absolute Continuity of Measures for Point Processes, and Filtering -- 20. Asymptotically Optimal Filtering 
653 |a Statistical Theory and Methods 
653 |a Statistics  
653 |a Probability Theory 
653 |a Probabilities 
700 1 |a Shiryaev, Albert N.  |e [author] 
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490 0 |a Stochastic Modelling and Applied Probability 
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082 0 |a 519.2 
520 |a 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 required mathematical background is presented in the first volume: the theory of martingales, stochastic differential equations, the absolute continuity of probability measures for diffusion and Ito processes, elements of stochastic calculus for counting processes. 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