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Pyrrho's lemma : ウィキペディア英語版
Pyrrho's lemma
In statistics, Pyrrho's lemma is the result that if one adds just one extra variable as a regressor from a suitable set to a linear regression model, one can get any desired outcome in terms of the coefficients (signs and sizes), as well as predictions, the R-squared, the t-statistics, prediction- and confidence-intervals. The argument for the coefficients was advanced by Herman Wold and Lars Juréen〔Wold, Herman and L. Juréen (1953) ''Demand Analysis: A Study in Econometrics'', John Wiley & Sons (2nd Ed)〕 but named, extended to include the other statistics and explained more fully by Theo Dijkstra. Dijkstra named it after the sceptic philosopher Pyrrho and concludes his article by noting that this lemma provides "some ground for a wide-spread scepticism concerning products of extensive datamining". One can only prove that a model 'works' by testing it on data different from the data that gave it birth. 〔(Dijkstra, p. 122)〕
The result has been discussed in the context of econometrics.〔Hendry, David F. (1995) ''Dynamic Econometrics'', Oxford University Press
== References ==



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