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- 2011-7-11
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2#
发表于 2011-7-13 16:24
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It's just saying that R2 will rise the and indicate a better fit as you add more independent variables but often times, the new variables do sh*t all for helping improve the predictability of the dependent variable but because of the way quants works, the R2 value goes up.
To adjust for this, you calculate adjusted R2 which is just deflated based on N-1/N-k-1 to compensate for the increased number of independent variables.
'Unlike R2, the adjusted R2 increases only if the new term improves the model more than would be expected by chance. The adjusted R2 can be negative, and will always be less than or equal to R2.' (From Wikipedia)
R2 adj = 1 - [ (n-1/n-k-1) x (1 - R2)] |
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