Statistical Inference for Fractional Diffusion Processes



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Éditeur :

Wiley


Collection :

Wiley Series in Probability and Statistics

Paru le : 2010-05-21



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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.
Pages
280 pages
Collection
Wiley Series in Probability and Statistics
Parution
2010-05-21
Marque
Wiley
EAN papier
9780470665688
EAN PDF
9780470667132

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
280
Taille du fichier
1239 Ko
Prix
108,61 €
EAN EPUB
9780470975763

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
280
Taille du fichier
1935 Ko
Prix
108,61 €