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Author: Ian W. McKeague Publisher: ISBN: Category : Languages : en Pages : 20
Book Description
The asymptotic behavior of the maximum likelihood estimator of a parameter in the drift term of a stationary ergodic diffusion process is studied under conditions in which the true drift function and the true noise function do not coincide with those specified by the parametric model. Originator-supplied key words include: Diffusion, Differential Equations.
Author: Ian W. McKeague Publisher: ISBN: Category : Languages : en Pages : 20
Book Description
The asymptotic behavior of the maximum likelihood estimator of a parameter in the drift term of a stationary ergodic diffusion process is studied under conditions in which the true drift function and the true noise function do not coincide with those specified by the parametric model. Originator-supplied key words include: Diffusion, Differential Equations.
Author: B. L. S. Prakasa Rao Publisher: John Wiley & Sons ISBN: 0470975768 Category : Mathematics Languages : en Pages : 213
Book Description
Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics. In model building, statistical inference for stochastic processes is of great importance from both a theoretical and an applications point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable. Key features: Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion. Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence. Presents a study of parametric and nonparametric inference problems for the fractional diffusion process. Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion. Includes recent results and developments in the area of statistical inference of fractional diffusion processes. Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.
Author: Yury A. Kutoyants Publisher: Springer Science & Business Media ISBN: 144713866X Category : Mathematics Languages : en Pages : 493
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: Erwin Bolthausen Publisher: Birkhäuser ISBN: 3034870264 Category : Mathematics Languages : en Pages : 392
Book Description
Pure and applied stochastic analysis and random fields form the subject of this book. The collection of articles on these topics represent the state of the art of the research in the field, with particular attention being devoted to stochastic models in finance. Some are review articles, others are original papers; taken together, they will apprise the reader of much of the current activity in the area.
Author: Alex Papanicolaou Publisher: ISBN: Category : Languages : en Pages : 48
Book Description
We provide a simple and easy to use goodness-of-fit test for the misspecification of the volatility function in diffusion models. The test uses power variations constructed as functionals of discretely observed diffusion processes. We introduce an orthogonality condition which stabilizes the limit law in the presence of parameter estimation and avoids the necessity for a bootstrap procedure that reduces performance and leads to complications associated with the structure of the diffusion process. The test has good finite sample performance as we demonstrate in numerical simulations.
Author: Yury A. Kutoyants Publisher: Springer Science & Business Media ISBN: 9401110204 Category : Mathematics Languages : en Pages : 308
Book Description
Small noise is a good noise. In this work, we are interested in the problems of estimation theory concerned with observations of the diffusion-type process Xo = Xo, 0 ~ t ~ T, (0. 1) where W is a standard Wiener process and St(') is some nonanticipative smooth t function. By the observations X = {X , 0 ~ t ~ T} of this process, we will solve some t of the problems of identification, both parametric and nonparametric. If the trend S(-) is known up to the value of some finite-dimensional parameter St(X) = St((}, X), where (} E e c Rd , then we have a parametric case. The nonparametric problems arise if we know only the degree of smoothness of the function St(X), 0 ~ t ~ T with respect to time t. It is supposed that the diffusion coefficient c is always known. In the parametric case, we describe the asymptotical properties of maximum likelihood (MLE), Bayes (BE) and minimum distance (MDE) estimators as c --+ 0 and in the nonparametric situation, we investigate some kernel-type estimators of unknown functions (say, StO,O ~ t ~ T). The asymptotic in such problems of estimation for this scheme of observations was usually considered as T --+ 00 , because this limit is a direct analog to the traditional limit (n --+ 00) in the classical mathematical statistics of i. i. d. observations. The limit c --+ 0 in (0. 1) is interesting for the following reasons.
Author: Peter C. B. Phillips Publisher: ISBN: Category : Languages : en Pages : 28
Book Description
This paper motivates and introduces a two-stage method for estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as recently developed in Barndorff-Nielsen and Shephard (2002), to provide a regression model for estimating the parameters in the diffusion function. In the second stage the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite sample performance of the proposed method is compared with that of the approximate maximum likelihood method of Aiuml;t-Sahalia (2002).
Author: National Research Council Publisher: National Academies Press ISBN: 0309076102 Category : Social Science Languages : en Pages : 286
Book Description
This volume is part of an effort to review what is known about the determinants of fertility transition in developing countries and to identify lessons that might lead to policies aimed at lowering fertility. It addresses the roles of diffusion processes, ideational change, social networks, and mass communications in changing behavior and values, especially as related to childbearing. A new body of empirical research is currently emerging from studies of social networks in Asia (Thailand, Taiwan, Korea), Latin America (Costa Rica), and Sub-Saharan Africa (Kenya, Malawi, Ghana). Given the potential significance of social interactions to the design of effective family planning programs in high-fertility settings, efforts to synthesize this emerging body of literature are clearly important.
Author: Ian W. McKeague
Author: Ian W. McKeague
Author: B. L. S. Prakasa Rao
Author: Yury A. Kutoyants
Author: Erwin Bolthausen
Author: Alex Papanicolaou
Author: Yury A. Kutoyants
Author: Carlo Bianchi
Author: Erik Lindström
Author: Peter C. B. Phillips
Author: National Research Council