Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Some Background on Ordinary Differential Equations
- 3 Pragmatic Introduction to Stochastic Differential Equations
- 4 Itô Calculus and Stochastic Differential Equations
- 5 Probability Distributions and Statistics of SDEs
- 6 Statistics of Linear Stochastic Differential Equations
- 7 Useful Theorems and Formulas for SDEs
- 8 Numerical Simulation of SDEs
- 9 Approximation of Nonlinear SDEs
- 10 Filtering and Smoothing Theory
- 11 Parameter Estimation in SDE Models
- 12 Stochastic Differential Equations in Machine Learning
- 13 Epilogue
- References
- Symbols and Abbreviations
- List of Examples
- List of Algorithms
- Index
8 - Numerical Simulation of SDEs
Published online by Cambridge University Press: 16 April 2019
Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Some Background on Ordinary Differential Equations
- 3 Pragmatic Introduction to Stochastic Differential Equations
- 4 Itô Calculus and Stochastic Differential Equations
- 5 Probability Distributions and Statistics of SDEs
- 6 Statistics of Linear Stochastic Differential Equations
- 7 Useful Theorems and Formulas for SDEs
- 8 Numerical Simulation of SDEs
- 9 Approximation of Nonlinear SDEs
- 10 Filtering and Smoothing Theory
- 11 Parameter Estimation in SDE Models
- 12 Stochastic Differential Equations in Machine Learning
- 13 Epilogue
- References
- Symbols and Abbreviations
- List of Examples
- List of Algorithms
- Index
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- Applied Stochastic Differential Equations , pp. 126 - 164Publisher: Cambridge University PressPrint publication year: 2019