Timeline for Assessing significance when measurements are correlated
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| S May 22, 2018 at 10:24 | history | bounty ended | CommunityBot | ||
| S May 22, 2018 at 10:24 | history | notice removed | CommunityBot | ||
| May 20, 2018 at 13:38 | comment | added | ReneBt | Following up on my comment to glagla's answer (sorry, didn't realise I'd put it there rather than the question), is it expected that variance tends the same side of 0,or would we be looking at covariance structures that have means close to 0 but mean magnitudes much larger? | |
| May 18, 2018 at 8:07 | answer | added | David Dale | timeline score: 1 | |
| May 17, 2018 at 17:32 | comment | added | Nat | You have training data consisting of noisy observations $y$ at locations $x$. You have a black box operation that takes your training data as inputs and returns an estimate $\hat{y}$ at locations $x$. You say $\hat{y}$ is "a set of correlated outputs". What is $\hat{y}$ correlated with? It is my understanding that $\hat{y}$ is a vector. | |
| May 14, 2018 at 16:24 | history | tweeted | twitter.com/StackStats/status/996063669959168000 | ||
| May 14, 2018 at 9:22 | answer | added | glagla | timeline score: 0 | |
| S May 14, 2018 at 8:50 | history | bounty started | rhombidodecahedron | ||
| S May 14, 2018 at 8:50 | history | notice added | rhombidodecahedron | Draw attention | |
| May 11, 2018 at 12:43 | history | asked | rhombidodecahedron | CC BY-SA 4.0 |