Timeline for Are inconsistent estimators ever preferable? A twist
Current License: CC BY-SA 4.0
12 events
| when toggle format | what | by | license | comment | |
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| May 19, 2020 at 12:00 | history | tweeted | twitter.com/StackStats/status/1262714663076278273 | ||
| May 19, 2020 at 1:19 | answer | added | user272422 | timeline score: 3 | |
| May 16, 2020 at 10:40 | vote | accept | Richard Hardy | ||
| May 5, 2020 at 6:20 | history | edited | Richard Hardy | CC BY-SA 4.0 |
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| May 4, 2020 at 21:24 | answer | added | Sextus Empiricus | timeline score: 3 | |
| May 4, 2020 at 20:08 | comment | added | Richard Hardy | @whuber, sorry, I am too tired and making mistakes tonight; should have gone to bed and continued tomorrow. I have edited once more, but I will come back tomorrow and see if this needs further editing. (Also, currently I do not see why we could not take the entire population instead of a sample without violating the definition of the loss function. But that can wait until tomorrow.) | |
| May 4, 2020 at 20:05 | history | edited | Richard Hardy | CC BY-SA 4.0 |
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| May 4, 2020 at 19:58 | comment | added | whuber♦ | What do you mean by "value of the objective function in population"? I thought we were discussing a loss function--and by definition, that's a function of a sample. | |
| May 4, 2020 at 19:28 | comment | added | Richard Hardy | @whuber, this is not what I meant. I might have misquoted your example. The pseudo-true value is meant to be a population characteristic that minimizes the value of the objective function in population and that the consistent estimator targets. I have updated my post accordingly. | |
| May 4, 2020 at 19:24 | history | edited | Richard Hardy | CC BY-SA 4.0 |
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| May 4, 2020 at 17:24 | comment | added | whuber♦ | I don't understand this question. Your characterization of a "pseudo-true parameter value" shows it to be a function of a sample, which cannot possibly be the target of any estimator. | |
| May 4, 2020 at 17:10 | history | asked | Richard Hardy | CC BY-SA 4.0 |