Timeline for PCA on correlation or covariance?
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Nov 22, 2014 at 17:51 | comment | added | Juancentro | Actually it is very reasonable to get 2 different answers when using PCA with correlation and covariance. In the stock case, it is a question of whether you should take betas (or standard deviation) into account | |
| Jun 27, 2013 at 15:00 | comment | added | whuber♦ | (-1) Getting "two different answers to the same problem" often just means you're bashing away mindlessly without thinking about which technique is appropriate for your analytical aims. It does not mean that one or (as you state) both techniques are not sensible, but only that at least one might not be appropriate for the problem or the data. Furthermore, in many cases you can anticipate that covariance-based PCA and correlation-based PCA should give different answers. After all, they are measuring different aspects of the data. Doing both by default would not make sense. | |
| S Jun 26, 2013 at 15:46 | review | Late answers | |||
| Jun 26, 2013 at 16:09 | |||||
| S Jun 26, 2013 at 15:46 | review | First posts | |||
| Jun 26, 2013 at 15:47 | |||||
| Jun 26, 2013 at 15:28 | history | answered | Lucozade | CC BY-SA 3.0 |