Nonlinear regression modeling for engineering applications : modeling, model validation, and enabling design of experiments
With a focus on practical applications, with relevant methods supported by fundamental analysis, this book details methods of nonlinear regression, computational algorithms, model validation, interpretation of residuals, and useful experimental design. --
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| Main Author | |
|---|---|
| Format | Electronic eBook |
| Language | English |
| Published |
Chichester, UK ; Hoboken, NJ :
John Wiley & Sons,
2016.
|
| Subjects | |
| Online Access | Full text |
| ISBN | 9781118597972 1118597974 1118597966 9781118597965 9781118597934 1118597931 9781118597958 1118597958 |
| Physical Description | 1 online resource |
Cover
Table of Contents:
- 1 Introductory Concepts
- 2 Model Types
- 3 Propagation of Uncertainty
- 4 Essential Probability and Statistics
- 5 Simulation
- 6 Steady and Transient State Detection
- 7 Regression Target
- Objective Function
- 8 Constraints
- 9 The Distortion of Linearizing Transforms
- 10 Optimization Algorithms
- 11 Multiple Optima
- 12 Regression Convergence Criteria
- 13 Model Design
- Desired and Undesired Model Characteristics and Effects
- 14 Data Pre- and Post-processing
- 15 Incremental Model Adjustment
- 16 Model and Experimental Validation
- 17 Model Prediction Uncertainty
- 18 Design of Experiments for Model Development and Validation
- 19 Utility versus Perfection
- 20 Troubleshooting
- 21 Case Studies.