Uncertainty
Quantification
Theory, Implementation, and Applications
Second Edition
Ralph C. Smith
This book was published by SIAM in the Computational Science and Engineering Series, CS30, 2024.
Click here to order the book.
If you have constructive comments or corrections, please contact me at rsmith@ncsu.edu.
List of Corrections to First Printing:
MA 540: Uncertainty Quantification for Physical and Biological Models, which uses this book:
Table
of Contents
Preface
Chapter 1. Introduction
MATLAB Codes
PART I: APPLICATIONS AND MODELS
Chapter 2. Applications
Chapter 3. Models and Data
PART II: PROBABILITY AND STATISTICS CONCEPTS
Chapter 4. Topics from Probability and Statistics
MATLAB
Codes
Chapter 5. Representation of Random Parameters and Fields
MATLAB Codes
Chapter 6. Observation Models
MATLAB Codes
PART III: PARAMETER SELECTION TECHNIQUES
Chapter 7. Parameter Identifiability and Influence
MATLAB Codes
Chapter 8. Local Sensitivity Analysis
MATLAB Codes
Chapter 9. Global Sensitivity Analysis
MATLAB codes
Chapter 10. Active Subspace Analysis
MATLAB Codes
PART IV: INVERSE AND FORWARD UNCERTAINTY
QUANTIFICATION
Chapter 11. Frequentist Parameter Interference
MATLAB Codes
Chapter 12. Bayesian Parameter Inference
MATLAB Codes
Chapter 13. Uncertainty Propagation for Model Responses
MATLAB Codes
Chapter 14. Model Discrepancy
MATLAB Codes
PART V: SURROGATE AND REDUCED-ORDER MODELS
Chapter 15. Surrogate Models
MATLAB Codes
Chapter 16. Numerical Surrogate Models
Chapter 17. Spectral Surrogates for Differential Equations
Chapter 18. Statistical Surrogate Models
Chapter 19. Reduced-Order Models
Chapter 20. Numerical and Statistical Integration Techniques
Appendix A. Supporting Material
