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Two-parameter Stochastic Processes With Finite Variation

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Two-parameter Stochastic Processes With Finite Variation

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Levy Processes & Stochastic Calculus

; necessary and sufficient conditions for Levy processes to have finite moments; characterisation of Levy processes with finite variation; Kunita's;

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Vector Integration and Stochastic Integration in Banach Spaces

two variables with finite semivariation, it explores the emergence of new classes of summable processes that make applications possible;

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Finite Markov Processes and Their Applications

introduction to the study of continuous parameter stochastic processes.;

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Theory and Statistical Applications of Stochastic Processes

This book is concerned with the theory of stochastic processes and the theoretical aspects of statistics for stochastic processes. It;

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Stochastic Analysis & Applications

of Large Numbers for Fuzzy Numbers with Unbounded Supports; On Moduli of Continuity for a Two-Parameter Fractional Lvy Brownian Motion on;

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Option Pricing with Long Memory Stochastic Volatility Models

propose two fractional continuous time stochastic volatility models which are built on the popular short memory stochastic volatility models;

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Finite Approximations in Discrete-Time Stochastic Control

and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence;

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Parameter Estimation in Fractional Diffusion Models

This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years;

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Linear Stochastic Systems

of stochastic linear systems, together with their interrelationships. The author first covers the foundations of linear stochastic systems and then;

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Levy Processes And Infinitely Divisible Distributions

Levy processes are rich mathematical objects and constitute perhaps the most basic class of stochastic processes with a continuous time;

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Levy Processes and Infinitely Divisible Distributions

Levy processes are rich mathematical objects and constitute perhaps the most basic class of stochastic processes with a continuous time;

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Telegraph Processes and Option Pricing

The telegraph process is a useful mathematical model for describing the stochastic motion of a particle that moves with finite speed on the;

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Introduction to Dynamics and Control in Mechanical Engineering Systems

dynamics The parallel developments of the Finite Element Methods in the 1950 s and the engineering applications of stochastic processes in the 1940;

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Stochastic Processes in Non-Archimedean Banach Spaces, Manifolds & Topological Groups

in stochastic processes with values in Banach spaces, manifolds and topological groups. Also discussed herein are random functions with values in Lie;

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Stochastic Structural Dynamics

dynamics The parallel developments of the Finite Element Methods in the 1950 s and the engineering applications of stochastic processes in the 1940;

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Stochastic Calculus for Quantitative Finance

variation, the theory of stochastic integration, definition and properties of the stochastic exponential; a part of the theory of Lvy processes;

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Reliability Assessment Using Stochastic Finite Element Analysis

The first complete guide to using the Stochastic Finite Element Method for reliability assessment Unlike other analytical reliability;

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Stochastic Finite Elements

particular attention to a spectral approach.Random system parameters are modeled as second-order stochastic processes, defined by their mean;

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Rethinking Parameters

of parameters in the process of language acquisition? The volume is organized into two parts. Part I ( The nature of variation and parameters;

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Stochastic Methods in Asset Pricing

monographs on stochastic processes and asset pricing, and it attempts to establish greater clarity on the connections between these two fields. The;

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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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Structured Dependence between Stochastic Processes

The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including;

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Reliability Calculations with the Stochastic Finite Element

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Sequential Stochastic Optimization

familiarity with discrete-parameter martingales. Major topics covered in Sequential Stochastic Optimization include: Fundamental notions, such as;

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Semimartingale Theory and Stochastic Calculus

Semimartingale Theory and Stochastic Calculus presents a systematic and detailed account of the general theory of stochastic processes, the;

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