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Malliavin Calculus and Stochastic Analysis

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Cover of 'Malliavin Calculus and Stochastic Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 An Application of Gaussian Measures to Functional Analysis
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    Chapter 2 Stochastic Taylor Formulas and Riemannian Geometry
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    Chapter 3 Local Invertibility of Adapted Shifts on Wiener Space and Related Topics
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    Chapter 4 Dilation Vector Field on Wiener Space
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    Chapter 5 The Calculus of Differentials for the Weak Stratonovich Integral
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    Chapter 6 Large Deviations for Hilbert-Space-Valued Wiener Processes: A Sequence Space Approach
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    Chapter 7 Stationary Distributions for Jump Processes with Inert Drift
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    Chapter 8 An Ornstein-Uhlenbeck-Type Process Which Satisfies Sufficient Conditions for a Simulation-Based Filtering Procedure
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    Chapter 9 Escape Probability for Stochastic Dynamical Systems with Jumps
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    Chapter 10 On the Stochastic Navier–Stokes Equation Driven by Stationary White Noise
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    Chapter 11 Malliavin Calculus and Stochastic Analysis
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    Chapter 12 Generalized Stochastic Heat Equations
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    Chapter 13 Gaussian Upper Density Estimates for Spatially Homogeneous SPDEs
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    Chapter 14 Stationarity of the Solution for the Semilinear Stochastic Integral Equation on the Whole Real Line
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    Chapter 15 A Strong Approximation of Subfractional Brownian Motion by Means of Transport Processes
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    Chapter 16 Malliavin Calculus for Fractional Heat Equation
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    Chapter 17 Malliavin Calculus and Stochastic Analysis
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    Chapter 18 Gradient Bounds for Solutions of Stochastic Differential Equations Driven by Fractional Brownian Motions
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    Chapter 19 Parameter Estimation for Fractional Ornstein–Uhlenbeck Processes with Discrete Observations
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    Chapter 20 The Effect of Competition on the Height and Length of the Forest of Genealogical Trees of a Large Population
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    Chapter 21 Linking Progressive and Initial Filtration Expansions
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    Chapter 22 A Malliavin Calculus Approach to General Stochastic Differential Games with Partial Information
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    Chapter 23 Asymptotics for the Length of the Longest Increasing Subsequence of a Binary Markov Random Word
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    Chapter 24 A Short Rate Model Using Ambit Processes
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    Chapter 25 Parametric Regularity of the Conditional Expectations via the Malliavin Calculus and Applications
Attention for Chapter 1: An Application of Gaussian Measures to Functional Analysis
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Chapter title
An Application of Gaussian Measures to Functional Analysis
Chapter number 1
Book title
Malliavin Calculus and Stochastic Analysis
Published by
Springer, Boston, MA, January 2013
DOI 10.1007/978-1-4614-5906-4_1
Book ISBNs
978-1-4614-5905-7, 978-1-4614-5906-4
Authors

Daniel W. Stroock, Stroock, Daniel W.