Chapter: Experimental Designs For First Order Models

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Home > Process Optimization: A Statistical Approach > Experimental Designs For First Order Models

Process Optimization: A Statistical Approach |

Enrique del Castillo

Springer US

Process Optimization: A Statistical Approach

Experimental Designs For First Order Models

Chapter Info

ARI Id

1664090179993_298066

Access

Not Available Free

Pages

45-83

DOI

10.1007/978-0-387-71435-6_3

Chapter URL

https://rd.springer.com/chapter/10.1007/978-0-387-71435-6_3

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Chapters/Headings	Author(s)	Pages	Info
Front Matter		i-xviii
Front Matter		2-2
An Overview of Empirical Process Optimization		3-25
Front Matter		28-28
Optimization Of First Order Models		29-43
Experimental Designs For First Order Models		45-83
Analysis and Optimization of Second Order Models		85-107
Experimental Designs for Second Order Models		109-156
Front Matter		158-158
Statistical Inference in First Order RSM Optimization		159-192
Statistical Inference in Second Order RSM Optimization		193-208
Bias Vs. Variance		209-219
Front Matter		222-222
Robust Parameter Design		223-278
Robust Optimization		279-287
Front Matter		290-290
Introduction to Bayesian Inference		291-319
Bayesian Methods for Process Optimization		321-364
Front Matter		366-366
Simulation Optimization		367-378
Chapters/Headings	Author(s)	Pages	Info

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