2.3.1.
Theoretical introduction
2.3.1.1. Purpose
2.3.1.2. Implementation in a nutshell
2.3.1.3. Limitation of PCA
Methodology
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Contents:
1. Glossary
2. Basic statistical elements
2.1. Random variable modelisation
2.2. Statistical treatments and operations
2.3. Combining these aspects: performing PCA
3. The Sampler module
4. Generating Surrogate Models
5. Sensitivity analysis
6. Dealing with optimisation issues
7. The Calibration module
8. The Uncertainty modeler module
Related Topics
Documentation overview
2.
Basic statistical elements
2.3.
Combining these aspects: performing PCA
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2.3.
Combining these aspects: performing PCA
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2.3.1.1.
Purpose
