Statistical Inference for Diffusion Type Processes

Kendall's Library of Statistics 8

B.L.S. Prakasa Rao (Autor)

Buch | Hardcover

366 Seiten

1999
John Wiley & Sons Inc (Verlag)
978-0-470-71112-5 (ISBN)

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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.

Bhagavatula Lakshmi Surya Prakasa Rao is an Indian statistician. He was born on 6 October 1942 in Porumamilla, Andhra Pradesh. He completed his B.A. course in Mathematics from Andhra University in 1960 and moved to the Indian Statistical Institute, Kolkata, where he completed his M.Stat in Statistics in 1962.

1. Diffusion Type Processes 2. Parametric Inference for Diffusion Type Processes from Continuous Paths

3. Parametric Inference for Diffusion Type Processes from Sampled Data

4. Nonparametric Inference for Diffusion Type Processes from Continuous Sample Paths

5. Nonparametric Inference for Diffusion Type Processes from Sampled Data

6. Applications to Stochastic Modeling

7. Numerical Approximation Methods for Stochastic Differential Equations

App. A. Uniform Ergodic Theorem

App. B. Stochastic Integration and Limit Theorems for Stochastic Integrals

App. C. Wavelets

App. D. Gronwall-Bellman Type Lemma

Erscheint lt. Verlag	17.5.2010
Verlagsort	New York
Sprache	englisch
Maße	166 x 240 mm
Gewicht	652 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Statistik
Themenwelt	Naturwissenschaften ► Biologie ► Botanik
ISBN-10	0-470-71112-4 / 0470711124
ISBN-13	978-0-470-71112-5 / 9780470711125
Zustand	Neuware