Timeline for Are there unbiased, non-linear estimators with lower variance than the OLS estimator?
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 10, 2023 at 0:35 | answer | added | ebuber | timeline score: 3 | |
| Jan 11, 2022 at 21:11 | answer | added | Dave | timeline score: 3 | |
| Dec 17, 2017 at 2:47 | history | tweeted | twitter.com/StackStats/status/942224733810110464 | ||
| Jul 4, 2017 at 6:24 | comment | added | Cagdas Ozgenc | If the underlying data generating process is i.i.d gaussian with a constant variance, and a linear mean model (basically the model matches the truth), in that case OLS is the minimum variance unbiased estimator, because it attains the Cramer Rao Lower Bound. Note that I didn't say minimum variance linear unbiased. Basically it is the best. econ.ohio-state.edu/dejong/note5.pdf. page 17. | |
| Jul 4, 2017 at 4:49 | comment | added | user126350 | Can you suggest why no such estimator $\tilde\beta$ exists? | |
| Jul 4, 2017 at 4:45 | comment | added | hejseb | Not under normality. If the error is e.g. Laplace distributed, the mean absolute deviation estimator is more efficient. | |
| Jul 4, 2017 at 4:05 | history | asked | user126350 | CC BY-SA 3.0 |