Statistical Inferences For Stochasic Processes

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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.

Statistical Inference In Stochastic Processes

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Author : Ishwar V. Basawa
language : en
Publisher:
Release Date : 1994

Statistical Inference In Stochastic Processes written by Ishwar V. Basawa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.

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.

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 Analysis Of Stochastic Processes In Time

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Author : J. K. Lindsey
language : en
Publisher: Cambridge University Press
Release Date : 2004-08-02

Statistical Analysis Of Stochastic Processes In Time written by J. K. Lindsey 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 2004-08-02 with Mathematics categories.

This book was first published in 2004. Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. This book introduces practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.

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.

Stochastic Epidemic Models With Inference

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Author : Tom Britton
language : en
Publisher: Springer Nature
Release Date : 2019-11-30

Stochastic Epidemic Models With Inference written by Tom Britton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-30 with Mathematics categories.

Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.

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.