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Stochastic Analysis of Mixed Fractional Gaussian Processes

Stochastic Analysis of Mixed Fractional Gaussian Processes presents the main tools necessary to characterize Gaussian processes. The book;

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Theory and Statistical Applications of Stochastic Processes

Gaussian processes, Ito integration, stochastic analysis, stochastic differential equations, fractional Brownian motion and parameter estimation;

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Stochastic Analysis & Applications

Contents: On the Large & Small Increments of Fractional Lvy Brownian Fields; On Oblique Reflecting Switched Diffusion Processes; On the;

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Analysis Of Fractional Stochastic Processes

This volume contains pedagogical, review and research level papers on fractional stochastic and quantum processes which have been the focus;

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Fractional Calculus and Fractional Processes with Applications to Financial Economics

calculus and fractional processes to asset pricing, financial time-series analysis, stochastic volatility modelling, and portfolio optimization;

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Statistical Inference for Fractional Diffusion Processes

point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus;

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Random Processes By Example

. The toolbox includes Gaussian processes, independently scattered measures such as Gaussian white noise and Poisson random measures, stochastic;

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Simulation of Stochastic Processes with Given Accuracy and Reliability

the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and;

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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Advances in Stochastic Structural Dynamics

during May 26-28, 2003. Topics include direct transfer substructure method for random response analysis, generation of bounded stochastic;

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Asymptotic Statistics

independent and identically distributed models and with stochastic processes. The book can be read in different ways, according to possibly;

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Stochastic Analysis, Stochastic Systems, And Applications To Finance

with the analysis of stochastic dynamical systems, in terms of Gaussian processes, white noise theory, and diffusion processes. The second part;

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Stable Non Gaussian Self Similar Processes with Stationary Increments

sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed;

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Fractional Signals and Systems

derivatives of stochastic processes. It is an essential reference for researchers in mathematics, physics, and engineering.;

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Selected Aspects of Fractional Brownian Motion

Fractional Brownian motion (fBm) is a stochastic process which deviates significantly from Brownian motion and semimartingales, and others;

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Selected Aspects of Fractional Brownian Motion

Fractional Brownian motion (fBm) is a stochastic process which deviates significantly from Brownian motion and semimartingales, and others;

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Stochastic Economic Dynamics

and rigorous treatment of uncertainty and its implications for describing stochastic processes by the stochastic differential equations of the;

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Stochastic Dynamics and Control

processes Random vibrations Structural reliability and fatigue, Non-Gaussian fatigue Monte Carlo methods Stochastic calculus;

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Gaussian Process Regression Analysis for Functional Data

analysis of batch data, repeated curves, and non-Gaussian data. Many flexible models based on Gaussian processes provide efficient ways of model;

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Simulation and Inference for Stochastic Processes with Yuima: A Comprehensive R Framework for Sdes and Other Stochastic Processes

supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic;

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Generalized Fractional Calculus

also great impact in numerical analysis, stochastics and fractional differential equations. The book continues with generalized fractional;

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Generalized Fractional Calculus

also great impact in numerical analysis, stochastics and fractional differential equations. The book continues with generalized fractional;

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Introduction To Sparse Stochastic Processes

stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating;

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Stochastic Calculus and Differential Equations for Physics and Finance

series analysis. Stochastic calculus is developed using general martingales. Scaling and fat tails are presented via diffusive models. Fractional;

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Potential Analysis of Stable Processes and its Extensions

probabilistic potential theory of stable stochastic processes, and, from the analytical point of view, of the fractional Laplacian. The introduction;

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Statistical Mechanics & Random Walks

; subordinated Gaussian processes; random walk models in biophysical science; non-equilibrium dynamics and diffusion processes; global random walk;

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