| 词条 | Pyrrho's lemma |
| 释义 |
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[1] but named, extended to include the other statistics and explained more fully by Theo Dijkstra.[2] 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. [3] The result has been discussed in the context of econometrics.[4] References1. ^Wold, Herman and L. Juréen (1953) Demand Analysis: A Study in Econometrics, John Wiley & Sons (2nd Ed) 2. ^{{cite journal | last1 = Dijkstra | first1 = Theo K | year = 1995 | title = Pyrrho's lemma, or have it your way | url = | journal = Metrika | volume = 42 | issue = 1| pages = 119–125 | doi = 10.1007/BF01894292 }} 3. ^(Dijkstra, p. 122) 4. ^Hendry, David F. (1995) Dynamic Econometrics, Oxford University Press 3 : Statistical theorems|Regression analysis|Lemmas |
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