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Nov 25, 2023 at 16:34 comment added picky_porpoise If there is no a priori knowledge of the mean, it is possible to prove that no loss function exists, see my answer to this question
Dec 18, 2020 at 8:14 vote accept Cagdas Ozgenc
Jun 26, 2017 at 7:22 comment added Cagdas Ozgenc @MichaelChernick There is nothing confusing about it. I provided the answer below, albeit with some restrictions (which were actually conjectured as part of the question).
Jun 26, 2017 at 7:14 answer added Cagdas Ozgenc timeline score: 4
Jan 25, 2017 at 15:46 history edited Cagdas Ozgenc CC BY-SA 3.0
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Dec 19, 2016 at 19:39 history edited Cagdas Ozgenc CC BY-SA 3.0
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Dec 18, 2016 at 19:31 history edited Cagdas Ozgenc CC BY-SA 3.0
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Dec 18, 2016 at 10:04 history edited Cagdas Ozgenc CC BY-SA 3.0
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Dec 18, 2016 at 9:25 history edited Cagdas Ozgenc CC BY-SA 3.0
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Dec 18, 2016 at 1:48 comment added Michael R. Chernick The question is confusing. First you say you want to predict Y given X and point out correctly that for squared error loss it is the best predictor. But then you pick VAR[Y|X]. Are you still trying to predict Y?
Dec 17, 2016 at 22:08 history asked Cagdas Ozgenc CC BY-SA 3.0