Omitting correlated variables
Data collected on the physical, biological or man-made world are often highly correlated, posing the question of whether fewer variables would contain almost as much information. A crude solution is simply to look at the Pearson correlation matrix and omit one of a pair of highly correlated variable...
| Published in: | ORiON |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Operations Research Society of South Africa (ORSSA)
2014-01-01
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| Online Access: | http://orion.journals.ac.za/pub/article/view/183 |