Statistical Inference for Ergodic Diffusion Processes PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Statistical Inference for Ergodic Diffusion Processes PDF full book. Access full book title Statistical Inference for Ergodic Diffusion Processes by Yury A. Kutoyants. Download full books in PDF and EPUB format.
Author: Yury A. Kutoyants
Publisher: Springer Science & Business Media
ISBN: 144713866X
Category : Mathematics
Languages : en
Pages : 493
Get Book Here
Book Description
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.
Author: Yury A. Kutoyants
Publisher: Springer Science & Business Media
ISBN: 144713866X
Category : Mathematics
Languages : en
Pages : 493
Get Book Here
Book Description
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.
Author: Christiane Fuchs
Publisher: Springer Science & Business Media
ISBN: 3642259693
Category : Mathematics
Languages : en
Pages : 439
Get Book Here
Book Description
Diffusion processes are a promising instrument for realistically modelling the time-continuous evolution of phenomena not only in the natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often carried out incorrectly, and the according statistical inference is considered almost exclusively by theoreticians. This book explains both topics in an illustrative way which also addresses practitioners. It provides a complete overview of the current state of research and presents important, novel insights. The theory is demonstrated using real data applications.
Author: Feng-yu Wang
Publisher: World Scientific
ISBN: 9814452661
Category : Mathematics
Languages : en
Pages : 392
Get Book Here
Book Description
Stochastic analysis on Riemannian manifolds without boundary has been well established. However, the analysis for reflecting diffusion processes and sub-elliptic diffusion processes is far from complete. This book contains recent advances in this direction along with new ideas and efficient arguments, which are crucial for further developments. Many results contained here (for example, the formula of the curvature using derivatives of the semigroup) are new among existing monographs even in the case without boundary.
Author: B.L.S. Prakasa Rao
Publisher: Wiley
ISBN: 9780470711125
Category : Mathematics
Languages : en
Pages : 0
Get Book Here
Book Description
Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question. Data collection, model building and inference from the data collected, validation of the model and refinement of the model are the key steps or building blocks involved in any rational decision making process. Stochastic processes are widely used for model building in the social, physical, engineering, and life sciences as well as in financial economics. Statistical inference for stochastic processes is of great importance from the theoretical as well as from applications point of view in model building. During the past twenty years, there has been a large amount of progress in the study of inferential aspects for continuous as well as discrete time stochastic processes. Diffusion type processes are a large class of continuous time processes which are widely used for stochastic modelling. the book aims to bring together several methods of estimation of parameters involved in such processes when the process is observed continuously over a period of time or when sampled data is available as generally feasible.
Author: Jaya P. N. Bishwal
Publisher: Springer
ISBN: 3540744487
Category : Mathematics
Languages : en
Pages : 271
Get Book Here
Book Description
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Author: Peter H. Baxendale
Publisher: World Scientific
ISBN: 9812706623
Category : Science
Languages : en
Pages : 416
Get Book Here
Book Description
The first paper in the volume, Stochastic Evolution Equations by N V Krylov and B L Rozovskii, was originally published in Russian in 1979. After more than a quarter-century, this paper remains a standard reference in the field of stochastic partial differential equations (SPDEs) and continues to attract attention of mathematicians of all generations, because, together with a short but thorough introduction to SPDEs, it presents a number of optimal and essentially non-improvable results about solvability for a large class of both linear and non-linear equations.
Author: Mathieu Kessler
Publisher: CRC Press
ISBN: 1439849765
Category : Mathematics
Languages : en
Pages : 507
Get Book Here
Book Description
The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th
Author: Robert S. Liptser
Publisher: Springer Science & Business Media
ISBN: 3662100282
Category : Mathematics
Languages : en
Pages : 409
Get Book Here
Book Description
"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW
Author: J. K. Lindsey
Publisher: Cambridge University Press
ISBN: 9781139454513
Category : Mathematics
Languages : en
Pages : 356
Get Book Here
Book Description
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.
Author: Daniel W. Stroock
Publisher: Springer
ISBN: 3540289992
Category : Mathematics
Languages : en
Pages : 338
Get Book Here
Book Description
From the reviews: "This book is an excellent presentation of the application of martingale theory to the theory of Markov processes, especially multidimensional diffusions. [...] This monograph can be recommended to graduate students and research workers but also to all interested in Markov processes from a more theoretical point of view." Mathematische Operationsforschung und Statistik
