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Statistical Inference for Diffusion Type Processes : Kendall's Library of Statistics by B. L. S. Prakasa Rao (2010, Hardcover)

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About this product

Product Identifiers

PublisherWiley & Sons, Incorporated, John

ISBN-100470711124

ISBN-139780470711125

eBay Product ID (ePID)92353903

Product Key Features

Number of Pages366 Pages

LanguageEnglish

Publication NameStatistical Inference for Diffusion Type Processes : Kendall's Library of Statistics

SubjectProbability & Statistics / General

Publication Year2010

TypeTextbook

Subject AreaMathematics

AuthorB. L. S. Prakasa Rao

FormatHardcover

Dimensions

Item Height1.1 in

Item Weight23.1 Oz

Item Length9.4 in

Item Width6.5 in

Additional Product Features

Intended AudienceScholarly & Professional

Volume NumberBk. 8

Table Of Content1. 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

SynopsisDecision 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., 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.