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st: r-squared in RREG procedure


From   Kit Baum <[email protected]>
To   [email protected]
Subject   st: r-squared in RREG procedure
Date   Fri, 7 Jul 2006 18:18:46 -0400

Thorstein wondered about the output from rreg.


. rreg price mpg rep78 headroom

Huber iteration 1: maximum difference in weights = .76806532
Huber iteration 2: maximum difference in weights = .22800273
Huber iteration 3: maximum difference in weights = .07985373
Huber iteration 4: maximum difference in weights = .1381678
Huber iteration 5: maximum difference in weights = .06184858
Huber iteration 6: maximum difference in weights = .02513437
Biweight iteration 7: maximum difference in weights = .27511851
Biweight iteration 8: maximum difference in weights = .16355823
Biweight iteration 9: maximum difference in weights = .21764717
Biweight iteration 10: maximum difference in weights = .09814313
Biweight iteration 11: maximum difference in weights = .05367749
Biweight iteration 12: maximum difference in weights = .00798559

Robust regression Number of obs = 69
F( 3, 65) = 7.40
Prob > F = 0.0002

------------------------------------------------------------------------ ------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
------------- +----------------------------------------------------------------
mpg | -113.8438 26.05671 -4.37 0.000 -165.8826 -61.80491
rep78 | 464.9123 143.1268 3.25 0.002 179.0684 750.7562
headroom | -176.2006 165.8466 -1.06 0.292 -507.4191 155.0179
_cons | 6395.867 897.0398 7.13 0.000 4604.355 8187.379
------------------------------------------------------------------------ ------

. ereturn list

scalars:
e(N) = 69
e(df_m) = 3
e(df_r) = 65
e(F) = 7.398391817218679
e(r2) = .2545459119347927
e(rmse) = 1069.508326203693
e(mss) = 25387908.37771961
e(rss) = 74350123.88823663
e(r2_a) = .2201403386394755


Both r^2 and adjusted r^2 are available; they just aren't appearing on the output. Same for RMSE.

Kit Baum, Boston College Economics
http://ideas.repec.org/e/pba1.html


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