Lifelines

- allow for multiple fitters to be passed into `k_fold_cross_validation`.
- statistical tests in `lifelines.statistics`. now return a `StatisticalResult` object with properties like `p_value`, `test_results`, and `summary`.
- fixed a bug in how log-rank statistical tests are performed. The covariance matrix was not being correctly calculated. This resulted in slightly different p-values.
- `WeibullFitter`, `ExponentialFitter`, `KaplanMeierFitter` and `BreslowFlemingHarringtonFitter` all have a `conditional_time_to_event_` property that measures the median duration remaining until the death event, given survival up until time t.

- addition of `median_` property to `WeibullFitter` and `ExponentialFitter`.
- `WeibullFitter` and `ExponentialFitter` will use integer timelines instead of float provided by `linspace`. This is
so if your work is to sum up the survival function (for expected values or something similar), it's more difficult to
make a mistake.

- Inclusion of the univariate fitters `WeibullFitter` and `ExponentialFitter`.
- Removing `BayesianFitter` from lifelines.
- Added new penalization scheme to AalenAdditiveFitter. You can now add a smoothing penalizer
that will try to keep subsequent values of a hazard curve close together. The penalizing coefficient
is `smoothing_penalizer`.
- Changed `penalizer` keyword arg to `coef_penalizer` in AalenAdditiveFitter.
- new `ridge_regression` function in `utils.py` to perform linear regression with l2 penalizer terms.
- Matplotlib is no longer a mandatory dependency.
- `.predict(time)` method on univariate fitters can now accept a scalar (and returns a scalar) and an iterable (and returns a numpy array)
- In `KaplanMeierFitter`, `epsilon` has been renamed to `precision`.

- New API for `CoxPHFitter` and `AalenAdditiveFitter`: the default arguments for `event_col` and `duration_col`. `duration_col` is now mandatory, and `event_col` now accepts a column, or by default, `None`, which assumes all events are observed (non-censored).
- Fix statistical tests.
- Allow negative durations in Fitters.
- New API in `survival_table_from_events`: `min_observations` is replaced by `birth_times` (default `None`).
- New API in `CoxPHFitter` for summary: `summary` will return a dataframe with statistics, `print_summary()` will print the dataframe (plus some other statistics) in a pretty manner.
- Adding "At Risk" counts option to univariate fitter `plot` methods, `.plot(at_risk_counts=True)`, and the function `lifelines.plotting.add_at_risk_counts`.
- Fix bug Epanechnikov kernel.

- move testing to py.test
- refactor tests into smaller files
- make `test_pairwise_logrank_test_with_identical_data_returns_inconclusive` a better test
- add test for summary()
- Alternate metrics can be used for `k_fold_cross_validation`.

- Lots of improvements to numerical stability (but something things still need work)
- Additions to `summary` in CoxPHFitter.
- Make all prediction methods output a DataFrame
- Fixes bug in 1-d input not returning in CoxPHFitter
- Lots of new tests.