84 lines
4.5 KiB
Python
84 lines
4.5 KiB
Python
""". regress totemp gnpdefl gnp unemp armed pop year
|
|
|
|
Source | SS df MS Number of obs = 16
|
|
-------------+------------------------------ F( 6, 9) = 330.29
|
|
Model | 184172402 6 30695400.3 Prob > F = 0.0000
|
|
Residual | 836424.129 9 92936.0144 R-squared = 0.9955
|
|
-------------+------------------------------ Adj R-squared = 0.9925
|
|
Total | 185008826 15 12333921.7 Root MSE = 304.85
|
|
|
|
------------------------------------------------------------------------------
|
|
totemp | Coef. Std. Err. t P>|t| [95% Conf. Interval]
|
|
-------------+----------------------------------------------------------------
|
|
gnpdefl | 15.06167 84.91486 0.18 0.863 -177.0291 207.1524
|
|
gnp | -.0358191 .033491 -1.07 0.313 -.111581 .0399428
|
|
unemp | -2.020229 .4883995 -4.14 0.003 -3.125065 -.9153928
|
|
armed | -1.033227 .2142741 -4.82 0.001 -1.517948 -.5485049
|
|
pop | -.0511045 .2260731 -0.23 0.826 -.5625173 .4603083
|
|
year | 1829.151 455.4785 4.02 0.003 798.7873 2859.515
|
|
_cons | -3482258 890420.3 -3.91 0.004 -5496529 -1467987
|
|
------------------------------------------------------------------------------
|
|
"""
|
|
|
|
|
|
#From Stata using Longley dataset as in the test and example for GLM
|
|
"""
|
|
. glm totemp gnpdefl gnp unemp armed pop year
|
|
|
|
Iteration 0: log likelihood = -109.61744
|
|
|
|
Generalized linear models No. of obs = 16
|
|
Optimization : ML Residual df = 9
|
|
Scale parameter = 92936.01
|
|
Deviance = 836424.1293 (1/df) Deviance = 92936.01
|
|
Pearson = 836424.1293 (1/df) Pearson = 92936.01
|
|
|
|
Variance function: V(u) = 1 [Gaussian]
|
|
Link function : g(u) = u [Identity]
|
|
|
|
AIC = 14.57718
|
|
Log likelihood = -109.6174355 BIC = 836399.2
|
|
|
|
------------------------------------------------------------------------------
|
|
| OIM
|
|
totemp | Coef. Std. Err. z P>|z| [95% Conf. Interval]
|
|
-------------+----------------------------------------------------------------
|
|
gnpdefl | 15.06167 84.91486 0.18 0.859 -151.3684 181.4917
|
|
gnp | -.0358191 .033491 -1.07 0.285 -.1014603 .029822
|
|
unemp | -2.020229 .4883995 -4.14 0.000 -2.977475 -1.062984
|
|
armed | -1.033227 .2142741 -4.82 0.000 -1.453196 -.6132571
|
|
pop | -.0511045 .2260731 -0.23 0.821 -.4941996 .3919906
|
|
year | 1829.151 455.4785 4.02 0.000 936.4298 2721.873
|
|
_cons | -3482258 890420.3 -3.91 0.000 -5227450 -1737066
|
|
------------------------------------------------------------------------------
|
|
"""
|
|
|
|
#RLM Example
|
|
|
|
"""
|
|
. rreg stackloss airflow watertemp acidconc
|
|
|
|
Huber iteration 1: maximum difference in weights = .48402478
|
|
Huber iteration 2: maximum difference in weights = .07083248
|
|
Huber iteration 3: maximum difference in weights = .03630349
|
|
Biweight iteration 4: maximum difference in weights = .2114744
|
|
Biweight iteration 5: maximum difference in weights = .04709559
|
|
Biweight iteration 6: maximum difference in weights = .01648123
|
|
Biweight iteration 7: maximum difference in weights = .01050023
|
|
Biweight iteration 8: maximum difference in weights = .0027233
|
|
|
|
Robust regression Number of obs = 21
|
|
F( 3, 17) = 74.15
|
|
Prob > F = 0.0000
|
|
|
|
------------------------------------------------------------------------------
|
|
stackloss | Coef. Std. Err. t P>|t| [95% Conf. Interval]
|
|
-------------+----------------------------------------------------------------
|
|
airflow | .8526511 .1223835 6.97 0.000 .5944446 1.110858
|
|
watertemp | .8733594 .3339811 2.61 0.018 .1687209 1.577998
|
|
acidconc | -.1224349 .1418364 -0.86 0.400 -.4216836 .1768139
|
|
_cons | -41.6703 10.79559 -3.86 0.001 -64.447 -18.89361
|
|
------------------------------------------------------------------------------
|
|
|
|
"""
|