Timeline for How are eigenvalues/singular values related to variance (SVD/PCA)?
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
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| Jul 29, 2020 at 13:26 | comment | added | whuber♦ | $x$ is literally any vector. That this is the formula for the variance is a consequence of its bilinearity properties. See stats.stackexchange.com/a/185000/919 or (for a more general and abstract explanation) math.stackexchange.com/a/3392345/1489. | |
| Jul 29, 2020 at 12:11 | vote | accept | the man | ||
| Jul 29, 2020 at 7:58 | comment | added | the man | Thanks for your answer. What exactly is the $p-$vector $x$ here (with respect to my data matrix)? Why is the variance defined like so? | |
| Jul 28, 2020 at 19:04 | history | answered | whuber♦ | CC BY-SA 4.0 |