Stochastic Processes Inference Theory
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Stochastic Processes Inference Theory
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Author : Malempati M. Rao
language : en
Publisher: Springer
Release Date : 2014-11-14
Stochastic Processes Inference Theory written by Malempati M. Rao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-14 with Mathematics categories.
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Statistical Inferences For Stochasic Processes
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Author : Ishwar V. Basawa
language : en
Publisher: Academic Press
Release Date : 1980-01-28
Statistical Inferences For Stochasic Processes written by Ishwar V. Basawa and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980-01-28 with Mathematics categories.
Introductory examples of stochastic models; Special models; General theory; Further approaches.
Simulation And Inference For Stochastic Processes With Yuima
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Author : Stefano M. Iacus
language : en
Publisher: Springer
Release Date : 2018-06-01
Simulation And Inference For Stochastic Processes With Yuima written by Stefano M. Iacus and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-01 with Computers categories.
The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.
Statistical Inference For Ergodic Diffusion Processes
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Author : Yu. A. Kutoyants
language : en
Publisher: Springer Science & Business Media
Release Date : 2004
Statistical Inference For Ergodic Diffusion Processes written by Yu. A. Kutoyants and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematics categories.
The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.
Statistical Inference From Stochastic Processes
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Author : Narahari Umanath Prabhu
language : en
Publisher: American Mathematical Soc.
Release Date : 1988
Statistical Inference From Stochastic Processes written by Narahari Umanath Prabhu and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Mathematics categories.
Comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. This book provides students and researchers with a familiarity with the foundations of inference from stochastic processes and intends to provide a knowledge of the developments.
Exponential Families Of Stochastic Processes
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Author : Uwe Küchler
language : en
Publisher: Springer Science & Business Media
Release Date : 1997-07-10
Exponential Families Of Stochastic Processes written by Uwe Küchler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-07-10 with Mathematics categories.
A comprehensive account of the statistical theory of exponential families of stochastic processes. The book reviews the progress in the field made over the last ten years or so by the authors - two of the leading experts in the field - and several other researchers. The theory is applied to a broad spectrum of examples, covering a large number of frequently applied stochastic process models with discrete as well as continuous time. To make the reading even easier for statisticians with only a basic background in the theory of stochastic process, the first part of the book is based on classical theory of stochastic processes only, while stochastic calculus is used later. Most of the concepts and tools from stochastic calculus needed when working with inference for stochastic processes are introduced and explained without proof in an appendix. This appendix can also be used independently as an introduction to stochastic calculus for statisticians. Numerous exercises are also included.
Stochastic Processes
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Author : Robert G. Gallager
language : en
Publisher: Cambridge University Press
Release Date : 2013-12-12
Stochastic Processes written by Robert G. Gallager and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-12 with Business & Economics categories.
The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.
Stochastic Processes And Applications
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Author : Grigorios A. Pavliotis
language : en
Publisher: Springer
Release Date : 2014-11-19
Stochastic Processes And Applications written by Grigorios A. Pavliotis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-19 with Mathematics categories.
This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.
Stationary Stochastic Processes
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Author : Georg Lindgren
language : en
Publisher: CRC Press
Release Date : 2012-10-01
Stationary Stochastic Processes written by Georg Lindgren and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-01 with Mathematics categories.
Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes. Features Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability Motivates mathematical theory from a statistical model-building viewpoint Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes Provides more than 100 exercises with hints to solutions and selected full solutions This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.
Probability Statistics And Stochastic Processes
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Author : Peter Olofsson
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-20
Probability Statistics And Stochastic Processes written by Peter Olofsson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-20 with Mathematics categories.
A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions. The next two chapters introduce limit theorems and simulation. Also included is a chapter on statistical inference with a section on Bayesian statistics, which is an important, though often neglected, topic for undergraduate-level texts. Markov chains in discrete and continuous time are also discussed within the book. More than 400 examples are interspersed throughout the text to help illustrate concepts and theory and to assist the reader in developing an intuitive sense of the subject. Readers will find many of the examples to be both entertaining and thought provoking. This is also true for the carefully selected problems that appear at the end of each chapter. This book is an excellent text for upper-level undergraduate courses. While many texts treat probability theory and statistical inference or probability theory and stochastic processes, this text enables students to become proficient in all three of these essential topics. For students in science and engineering who may take only one course in probability theory, mastering all three areas will better prepare them to collect, analyze, and characterize data in their chosen fields.