[SciPy-User] statsmodels - rlm

[Jeff Reback]

Hi,
 
Is their a way to recover the final Results class in a robust estimation?
 
see below - I can clearly replicate the WLS regression and get a Results class with the correct results;
is their a reference in the RLMResults class (that points to the wls_results) that I am missing?
 
thanks,
 
Jeff
 
# using v2 of statsmodels
import numpy as np
import scikits.statsmodels as sm
 
#delivery time(minutes)    
endog = np.array([16.68, 11.50, 12.03, 14.88, 13.75, 18.11, 8.00, 17.83,    
                  79.24, 21.50, 40.33, 21.00, 13.50, 19.75, 24.00, 29.00, 15.35, 19.00,    
                  9.50, 35.10, 17.90, 52.32, 18.75, 19.83, 10.75])
 
#number of cases, distance (Feet)    
exog = np.array([[7, 3, 3, 4, 6, 7, 2, 7, 30, 5, 16, 10, 4, 6, 9, 10, 6, 7, 3, 17, 10, 26, 9, 8, 4], 
                 [560, 220, 340, 80, 150, 330, 110, 210, 1460, 605, 688, 215, 255, 462, 448, 776, 200, 132, 36, 770, 140, 810, 450, 635,150]])

exog = exog.T    
exog = sm.add_constant(exog)
rlm  = sm.RLM(endog, exog).fit()
print "RLM params -> %s, r2 -> %s" % (rlm.params, getattr(rlm,'rsquared',None))
wls  = sm.WLS(endog, exog, weights = rlm.weights).fit()
print "WLS params -> %s, r2 -> %s" % (wls.params, wls.rsquared) 
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