This volume presents a mathematical treatment of classical inference theory (Neyman-Pearson, Fisher and Wald) from the perspective of using it in stochastic processes, including some generalizations. It includes analysis of likelihood ratios for both Gaussian and several other classes (infinitely divisible, jump Markov, diffusion and additive). Both linear and non-linear filtering (also for general non-quadratic 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 also included. The text is designed to be useful to researchers and graduate students working in mathematics, statistics, and systems and communication engineering.
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`This is an impressive book ... of high mathematical quality and is written in a format with theorems and proofs. Each chapter ends with bibliographical notes, complements and exercises. The latter make the book also interesting for teaching graduate courses.'
Publication of the International Statistical Institute
`Overall, the topics included cover a broad spectrum of processes and inference methods in a fairly comprehensive manner and in depth. The book is highly recommended reading.'
Mathematical Reviews, 2002b
Preface. I. Introduction and Preliminaries. II. Some Principles of Hypothesis Testing. III. Parameter Estimation and Asymptotics. IV. Inferences for Classes of Processes. V. Likelihood Ratios for Processes. VI. Sampling Methods for Processes. VII. More on Stochastic Inference. VIII. Prediction and Filtering of Processes. IX. Nonparametric Estimation for Processes. Bibliography. Notation index. Author index. Subject index.
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Da: Better World Books, Mishawaka, IN, U.S.A.
Condizione: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Codice articolo 68667804-6
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