Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes PDF Author: Uwe Küchler
Publisher: Springer Science & Business Media
ISBN: 0387227652
Category : Mathematics
Languages : en
Pages : 325

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Book Description
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.

Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes PDF Author: Uwe Küchler
Publisher: Springer Science & Business Media
ISBN: 0387227652
Category : Mathematics
Languages : en
Pages : 325

Get Book Here

Book Description
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.

Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes PDF Author: Uwe Kuchler
Publisher:
ISBN: 9781475770995
Category :
Languages : en
Pages : 336

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Book Description


Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes PDF Author: U. Küchler
Publisher:
ISBN:
Category :
Languages : en
Pages : 40

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Book Description


Exponential Families of Stochastic Processes

Exponential Families of Stochastic Processes PDF Author: Uwe Küchler
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Statistical Modelling by Exponential Families

Statistical Modelling by Exponential Families PDF Author: Rolf Sundberg
Publisher: Cambridge University Press
ISBN: 1108476597
Category : Business & Economics
Languages : en
Pages : 297

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Book Description
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.

Semimartingales and their Statistical Inference

Semimartingales and their Statistical Inference PDF Author: B.L.S. Prakasa Rao
Publisher: CRC Press
ISBN: 9781584880080
Category : Mathematics
Languages : en
Pages : 684

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Book Description
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include: Asymptotic likelihood theory Quasi-likelihood Likelihood and efficiency Inference for counting processes Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.

Stochastic Processes: Theory and Methods

Stochastic Processes: Theory and Methods PDF Author: D N Shanbhag
Publisher: Gulf Professional Publishing
ISBN: 9780444500144
Category : Mathematics
Languages : en
Pages : 990

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Book Description
This volume in the series contains chapters on areas such as pareto processes, branching processes, inference in stochastic processes, Poisson approximation, Levy processes, and iterated random maps and some classes of Markov processes. Other chapters cover random walk and fluctuation theory, a semigroup representation and asymptomatic behavior of certain statistics of the Fisher-Wright-Moran coalescent, continuous-time ARMA processes, record sequence and their applications, stochastic networks with product form equilibrium, and stochastic processes in insurance and finance. Other subjects include renewal theory, stochastic processes in reliability, supports of stochastic processes of multiplicity one, Markov chains, diffusion processes, and Ito's stochastic calculus and its applications. c. Book News Inc.

Statistical Inference from Stochastic Processes

Statistical Inference from Stochastic Processes PDF Author: Narahari Umanath Prabhu
Publisher: American Mathematical Soc.
ISBN: 0821850873
Category : Mathematics
Languages : en
Pages : 406

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Book Description
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.

Fundamentals of Statistical Exponential Families

Fundamentals of Statistical Exponential Families PDF Author: Lawrence D. Brown
Publisher: IMS
ISBN: 9780940600102
Category : Business & Economics
Languages : en
Pages : 302

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Book Description


Essentials of Stochastic Processes

Essentials of Stochastic Processes PDF Author: Richard Durrett
Publisher: Springer
ISBN: 3319456148
Category : Mathematics
Languages : en
Pages : 282

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Book Description
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatment of other topics useful for applications has been expanded. In addition, the ordering of topics has been improved; for example, the difficult subject of martingales is delayed until its usefulness can be applied in the treatment of mathematical finance.