Timeline for In simple linear regression, what is the covariance between the error term and the residual?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
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| Mar 26, 2018 at 1:07 | comment | added | Ben | The terms $\beta_0$ and $\beta_1$ depend on $\varepsilon_1, ..., \varepsilon_n$, so the removal of these terms from the covariance is invalid. | |
| Apr 21, 2014 at 4:20 | history | edited | bdeonovic | CC BY-SA 3.0 |
added 32 characters in body
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| Apr 21, 2014 at 4:09 | history | edited | bdeonovic | CC BY-SA 3.0 |
added 13 characters in body
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| Apr 21, 2014 at 3:56 | history | edited | Nick Stauner | CC BY-SA 3.0 |
$\TeX$, punctuation, capitalization
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| Apr 21, 2014 at 3:49 | comment | added | user2350622 | But should the last line be $\text{Cov}[\epsilon_i, \epsilon_i] = \sigma^2$ by gauss markov conditions? | |
| Apr 21, 2014 at 3:19 | history | answered | bdeonovic | CC BY-SA 3.0 |