R help - Nov 2014 - How are the standard errors of the estimates in glm.nb() calculated?

Hello, I am running a negative binomial model using the glm.nb function in MASS
package. But the standard errors I get are slightly different from the same
model I ran using Stata's nbreg command. Some of the standard errors are the
same, but some are not. Those that are different differ in their decimals,
particularly the third decimal. I am wondering how exactly glm.nb calculates
standard errors. I could not find any documentation. The standard errors in
Stata's nbreg command are calculated from the observed information matrix. I
am thinking that maybe glm.nb uses the expected information instead of the
observed information? But I could not figure out if that is the case. It may be
because I don't have a very good grasp of the difference between expected
and observed information. I also tried to look into the source code of glm.nb by
typing glm.nb in the R console, but I could not find how the standard errors are
calculated. Any help will be very much appreciated! As a side note, here is the
output I get after running the glm.nb model: Deviance Residuals:     Min      
1Q         Median       3Q      Max   -2.8076  -1.0216  -0.4800   0.3257  
4.2359   Coefficients:                                 Estimate    Std. Error   
z value   Pr(>|z|)     (Intercept)             -1.4211390   0.2334931  
-6.086   1.15e-09 *** x1                        -0.0633597    0.1825984   -0.347
0.728599     x2                         0.0240531    0.0327962    0.733    
0.463308     x3                        -0.0223691    0.0318900   -0.701   
0.483025     x4                        0.1004497     0.0348040    2.886    
0.003900 ** x5                        -0.0110895    0.0254989   -0.435   
0.663635     x6                        0.0098525     0.0174814    0.564    
0.573029     x7                        -0.2574358    0.2375014   -1.084    
0.278394     x8                        0.0319359     0.0250482   1.275     
0.202318     x9                         0.9795687     0.0332084  29.498    
< 2e-16 *** x10                       -1.2697342   0.1684822   -7.536    
4.83e-14 *** x11                       0.0021235    0.0003019   7.035    
2.00e-12 *** x12                       0.5223974    0.2052481   2.545     
0.010922 *   x13                      -0.0491496   0.1853978   -0.265    
0.790930     x14                      -0.4071932    0.1087920  -3.743    
0.000182 *** x15                      -0.2980707   0.2197779   -1.356    
0.175024     x16                      -0.2374620   0.1885971    -1.259   
0.207995     x17                      -0.1466253   0.1236171    -1.186   
0.235573     --- Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for Negative Binomial(1.2214) family taken to be 1)     
Null deviance: 3658.9  on 1108  degrees of freedom Residual deviance: 1186.1  on
1091  degrees of freedom   (34 observations deleted due to missingness) AIC:
5104.4 Number of Fisher Scoring iterations: 1               Theta:  1.2214      
Std. Err.:  0.0855  2 x log-likelihood:  -5066.3860

	[[alternative HTML version deleted]]