Some failing CoxPH tests

Noticed some strange behavior with CoxPH. I always have
normalized data, which did not seem to work good with
the implementation. The failures here seem unrelated to that
though.

The added tests currently fail with the following trace:

>Traceback (most recent call last):
>  File "/home/jonas/workspacepython/lifelines/lifelines/tests/test_suite.py", line 937, in test_crossval_normalized
>    event_col='E', k=3)
>  File "/home/jonas/workspacepython/lifelines/lifelines/utils.py", line 311, in k_fold_cross_validation
>    fitter.fit(training_data, duration_col=duration_col, event_col=event_col)
>  File "/home/jonas/workspacepython/lifelines/lifelines/estimation.py", line 998, in fit
>    include_likelihood=include_likelihood)
>  File "/home/jonas/workspacepython/lifelines/lifelines/estimation.py", line 938, in _newton_rhaphson
>    delta = solve(-hessian, step_size * gradient.T)
>  File "/home/jonas/anaconda3/lib/python3.4/site-packages/numpy/linalg/linalg.py", line 381, in solve
>    r = gufunc(a, b, signature=signature, extobj=extobj)
>  File "/home/jonas/anaconda3/lib/python3.4/site-packages/numpy/linalg/linalg.py", line 90, in _raise_linalgerror_singular
>    raise LinAlgError("Singular matrix")
>numpy.linalg.linalg.LinAlgError: Singular matrix

However, note that I have commented out one of the datasets because that
seems to cause the cross-validation to end up in an infinite loop of
some kind. The tests never finish (only waited for ~2 minutes).

Doing similar things with *R* works with no problem.

Doing the following is a fast way to check the results:

    python -m unittest lifelines.tests.test_suite.CoxRegressionTests
From some articles I've read and from my personal experience, the c-index of survival models is never very high. I ran some tests where I knew exactly a few hundred survival functions, computed the medians of each one, and generated a random variable generated from each survival function, then ran this data through the c-index, with the RV as the actual and the median as my guess (which would be a perfect case in practice). By averaging over many trials of this, I got an average c-index of 0.62-0.63