Timeline for Sufficient Statistic for $\beta$ in OLS
Current License: CC BY-SA 4.0
12 events
| when toggle format | what | by | license | comment | |
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| Mar 27, 2019 at 10:27 | answer | added | Anselmo Alves de Sousa | timeline score: 0 | |
| S Nov 12, 2018 at 7:29 | history | bounty ended | Cagdas Ozgenc | ||
| S Nov 12, 2018 at 7:29 | history | notice removed | Cagdas Ozgenc | ||
| Nov 12, 2018 at 7:29 | vote | accept | Cagdas Ozgenc | ||
| Nov 8, 2018 at 12:00 | history | tweeted | twitter.com/StackStats/status/1060502357497274368 | ||
| Nov 8, 2018 at 10:31 | answer | added | Ben | timeline score: 16 | |
| Nov 6, 2018 at 8:48 | history | edited | Ferdi |
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| S Nov 6, 2018 at 7:50 | history | bounty started | Cagdas Ozgenc | ||
| S Nov 6, 2018 at 7:50 | history | notice added | Cagdas Ozgenc | Draw attention | |
| Nov 2, 2018 at 12:26 | comment | added | CloseToC | Sufficiency of an estimator means that the data is uninformative about $\beta$ given the estimator. If the full rank condition fails here, then $\beta$ is not uniquely identified. This means there is a $\beta^*$ different from $\beta$ such that $\Pr_{\beta^*}(y \leq t) = Pr_{\beta}(y \leq t)$ for all $t$. The data as a whole is not informative about whether the parameter is equal to $\beta$ or $\beta^*$, so it also isn't conditional on some function of it. | |
| Nov 2, 2018 at 11:40 | history | edited | Cagdas Ozgenc | CC BY-SA 4.0 |
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| Nov 2, 2018 at 11:18 | history | asked | Cagdas Ozgenc | CC BY-SA 4.0 |