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Matches in Library of Congress for { <http://lccn.loc.gov/00039096> ?p ?o. }

• 00039096 contributor B30614.
• 00039096 created "c2000.".
• 00039096 date "2000".
• 00039096 date "c2000.".
• 00039096 dateCopyrighted "c2000.".
• 00039096 description "Includes bibliographical references (p. 601-625) and indexes.".
• 00039096 description "Machine generated contents note: Chapter I: Introduction and Preliminaries 1 -- 1.1 The problem of inference1 -- 1.2 Testing a hypothesis4 -- 1.3 Distinguishability of hypotheses7 -- 1.4 Estimation of parameters10 -- 1.5 Inference as a decision problem12 -- 1.6 Complements and exercises15 -- Bibliographical notes17 -- Chapter II: Some Principles of Hypothesis Testing 19 -- 2.1 Testing simple hypotheses19 -- 2.2 Reduction of composite hypotheses38 -- 2.3 Composite hypotheses with iterated weights42 -- 2.4 Bayesian methodology for applications 48 -- 2.5 Further results on composite hypotheses55 -- 2.6 Complements and exercises67 -- Bibliographical notes70 -- Chapter III: Parameter Estimation and Asymptotics 73 -- 3.1 Loss functions of different types 73 -- 3.2 Existence and other properties of estimators75 -- 3.3 Some principles of estimation 88 -- 3.4 Asymptotics in estimation methodology107 -- 3.5 Sequential estimation117 -- 3.6 Complements and exercises125 -- Bibliographical notes130 -- Chapter IV: Inferences for Classes of Processes 133 -- 4.1 Testing methods for second order processes133 -- 4.2 Sequential testing of processes155 -- 4.3 Weighted unbiased linear least squares prediction179 -- 4.4 Estimation in discrete parameter models196 -- 4.5 Asymptotic properties of estimators200 -- 4.6 Complements and exercises213 -- Bibliographical notes219 -- Chapter V: Likelihood Ratios for Processes 223 -- 5.1 Sets of admissible signals or translates223 -- 5.2 General Gaussian processes247 -- 5.3 Independent increment and jump Markov processes. 277 -- 5.4 Infinitely divisible processes298 -- 5.5 Diffusion type processes 314 -- 5.6 Complements and exercises327 -- Bibliographical notes335 -- Chapter VI: Sampling Methods for Processes 339 -- 6.1 Kotel'nikov-Shannon methodology339 -- 6.2 Band limited sampling348 -- 6.3 Analyticity of second order processes353 -- 6.4 Periodic sampling of processes and fields358 -- 6.5 Remarks on optional sampling374 -- 6.6 Complements and exercises375 -- Bibliographical notes380 -- Chapter VII: More on Stochastic Inference 383 -- 7.1 Absolute continuity of families of probability measures 383 -- 7.2 Likelihood ratios for families of non Gaussian measures 405 -- 7.3 Extension to two parameter families of measures413 -- 7.4 Likelihood ratios in statistical communication theory 429 -- 7.5 The general Gaussian dichotomy and Girsanov's theorem 435 -- 7.6 Complements and exercises452 -- Bibliographical notes462 -- Chapter VIII: Prediction and Filtering of Processes 465 -- 8.1 Predictors and projections465 -- 8.2 Least squares prediction: the Cram6r-Hida approach 480 -- 8.3 Linear filtering: Bochner's formulatioii488 -- 8.4 Kalman-Bucy filters: the linear case/509 -- 8.5 Kalman-Bucy filters: the nonlinear case535 -- 8.6 Complements and exercises549 -- Bibliographical notes553 -- Chapter IX: Nonparametric Estimation for Processes 557 -- 9.1 Spectra for classes of second order processes557 -- 9.2 Asymptotically unbiased estimation of bispectra560 -- 9.3 Resampling procedure and consistent estimation563 -- 9.4 Associated spectral estimation for a class of processes 572 -- 9.5 Limit distributions of (bi)spectral function estimators .583 -- 9.6 Complements and exercises593 -- Bibliographical notes597 -- Bibliography 601 -- Notation index 627 -- Author index 633 -- Subject index 639.".
• 00039096 extent "xvi, 645 p. :".
• 00039096 identifier "0792363248 (alk. paper)".
• 00039096 identifier 00039096-d.html.
• 00039096 identifier 00039096.html.
• 00039096 isPartOf "Mathematics and its applications (Kluwer Academic Publishers) ; v. 508.".
• 00039096 isPartOf "Mathematics and its applications ; v. 508".
• 00039096 issued "2000".
• 00039096 issued "c2000.".
• 00039096 language "eng".
• 00039096 publisher "Dordrecht ; Boston : Kluwer Academic Publishers,".
• 00039096 subject "519.2/3 21".
• 00039096 subject "Mathematical statistics.".
• 00039096 subject "QA274 .R373 2000".
• 00039096 subject "Stochastic processes.".
• 00039096 tableOfContents "Machine generated contents note: Chapter I: Introduction and Preliminaries 1 -- 1.1 The problem of inference1 -- 1.2 Testing a hypothesis4 -- 1.3 Distinguishability of hypotheses7 -- 1.4 Estimation of parameters10 -- 1.5 Inference as a decision problem12 -- 1.6 Complements and exercises15 -- Bibliographical notes17 -- Chapter II: Some Principles of Hypothesis Testing 19 -- 2.1 Testing simple hypotheses19 -- 2.2 Reduction of composite hypotheses38 -- 2.3 Composite hypotheses with iterated weights42 -- 2.4 Bayesian methodology for applications 48 -- 2.5 Further results on composite hypotheses55 -- 2.6 Complements and exercises67 -- Bibliographical notes70 -- Chapter III: Parameter Estimation and Asymptotics 73 -- 3.1 Loss functions of different types 73 -- 3.2 Existence and other properties of estimators75 -- 3.3 Some principles of estimation 88 -- 3.4 Asymptotics in estimation methodology107 -- 3.5 Sequential estimation117 -- 3.6 Complements and exercises125 -- Bibliographical notes130 -- Chapter IV: Inferences for Classes of Processes 133 -- 4.1 Testing methods for second order processes133 -- 4.2 Sequential testing of processes155 -- 4.3 Weighted unbiased linear least squares prediction179 -- 4.4 Estimation in discrete parameter models196 -- 4.5 Asymptotic properties of estimators200 -- 4.6 Complements and exercises213 -- Bibliographical notes219 -- Chapter V: Likelihood Ratios for Processes 223 -- 5.1 Sets of admissible signals or translates223 -- 5.2 General Gaussian processes247 -- 5.3 Independent increment and jump Markov processes. 277 -- 5.4 Infinitely divisible processes298 -- 5.5 Diffusion type processes 314 -- 5.6 Complements and exercises327 -- Bibliographical notes335 -- Chapter VI: Sampling Methods for Processes 339 -- 6.1 Kotel'nikov-Shannon methodology339 -- 6.2 Band limited sampling348 -- 6.3 Analyticity of second order processes353 -- 6.4 Periodic sampling of processes and fields358 -- 6.5 Remarks on optional sampling374 -- 6.6 Complements and exercises375 -- Bibliographical notes380 -- Chapter VII: More on Stochastic Inference 383 -- 7.1 Absolute continuity of families of probability measures 383 -- 7.2 Likelihood ratios for families of non Gaussian measures 405 -- 7.3 Extension to two parameter families of measures413 -- 7.4 Likelihood ratios in statistical communication theory 429 -- 7.5 The general Gaussian dichotomy and Girsanov's theorem 435 -- 7.6 Complements and exercises452 -- Bibliographical notes462 -- Chapter VIII: Prediction and Filtering of Processes 465 -- 8.1 Predictors and projections465 -- 8.2 Least squares prediction: the Cram6r-Hida approach 480 -- 8.3 Linear filtering: Bochner's formulatioii488 -- 8.4 Kalman-Bucy filters: the linear case/509 -- 8.5 Kalman-Bucy filters: the nonlinear case535 -- 8.6 Complements and exercises549 -- Bibliographical notes553 -- Chapter IX: Nonparametric Estimation for Processes 557 -- 9.1 Spectra for classes of second order processes557 -- 9.2 Asymptotically unbiased estimation of bispectra560 -- 9.3 Resampling procedure and consistent estimation563 -- 9.4 Associated spectral estimation for a class of processes 572 -- 9.5 Limit distributions of (bi)spectral function estimators .583 -- 9.6 Complements and exercises593 -- Bibliographical notes597 -- Bibliography 601 -- Notation index 627 -- Author index 633 -- Subject index 639.".
• 00039096 title "Stochastic processes : inference theory / by M.M. Rao.".
• 00039096 type "text".