Surrogates : Gaussian process modeling, design, and optimization for the applied sciences /
| Main Author: | |
|---|---|
| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
CRC Press,
[2020]
|
| Series: | Texts in statistical science.
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Historical perspective
- Four motivating datasets
- Steepest ascent and ridge analysis
- Space-filling design
- Gaussian process regression
- Model-based design for GPs
- Optimization
- Calibration and sensitivity
- GP fidelity and scale
- Heteroskedasticity.