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Engineering Optimization: Applications, Methods, and Analysis

By
R. Russell Rhinehart
R. Russell Rhinehart
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ISBN:
9781118936337
No. of Pages:
770
Publisher:
ASME Press
Publication date:
2018

This chapter is a summary of key issues and solutions related to nonlinear regression–fitting nonlinear models to data. The details of diverse issues are revealed in the book Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments by Rhinehart, R. R., John Wiley & Sons, Inc., Hoboken, NJ, 2016b. Here, they are summarized and presented with an optimization application perspective.

29.1
Introduction
29.2
Perspective
29.3
Least Squares Regression: Traditional View on Linear Model Parameters
29.4
Models Nonlinear in DV
29.5
Maximum Likelihood
29.6
Convergence Criterion
29.7
Model Order or Complexity
29.8
Bootstrapping to Reveal Model Uncertainty
29.9
Perspective
29.10
Takeaway
29.11
Exercises
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