Lifelines

- fixed confidence intervals in cumulative hazards for parametric univarite models. They were previously
serverly depressed.
- adding left-truncation support to parametric univarite models with the `entry` kwarg in `.fit`

- Some performance improvements to parametric univariate models.
- Suppressing some irrelevant NumPy and autograd warnings, so lifeline warnings are more noticeable.
- Improved some warning and error messages.

- New univariate fitter `PiecewiseExponentialFitter` for creating a stepwise hazard model. See docs online.
- Ability to create novel parametric univariate models using the new `ParametericUnivariateFitter` super class. See docs online for how to do this.
- Unfortunately, parametric univariate fitters are not serializable with `pickle`. The library `dill` is still useable.
- Complete overhaul of all internals for parametric univariate fitters. Moved them all (most) to use `autograd`.
- `LogNormalFitter` no longer models `log_sigma`.

- bug fixes in `LogNormalFitter` variance estimates
- improve convergence of `LogNormalFitter`. We now model the log of sigma internally, but still expose sigma externally.
- use the `autograd` lib to help with gradients.
- New `LogLogisticFitter` univariate fitter available.

- `LogNormalFitter` is a new univariate fitter you can use.
- `WeibullFitter` now correctly returns the confidence intervals (previously returned only NaNs)
- `WeibullFitter.print_summary()` displays p-values associated with its parameters not equal to 1.0 - previously this was (implicitly) comparing against 0, which is trivially always true (the parameters must be greater than 0)
- `ExponentialFitter.print_summary()` displays p-values associated with its parameters not equal to 1.0 - previously this was (implicitly) comparing against 0, which is trivially always true (the parameters must be greater than 0)
- `ExponentialFitter.plot` now displays the cumulative hazard, instead of the survival function. This is to make it easier to compare to `WeibullFitter` and `LogNormalFitter`
- Univariate fitters' `cumulative_hazard_at_times`, `hazard_at_times`, `survival_function_at_times` return pandas Series now (use to be numpy arrays)
- remove `alpha` keyword from all statistical functions. This was never being used.
- Gone are astericks and dots in `print_summary` functions that represent signficance thresholds.
- In models' `summary` (including `print_summary`), the `log(p)` term has changed to `-log2(p)`. This is known as the s-value. See https://lesslikely.com/statistics/s-values/
- introduce new statistical tests between univariate datasets: `survival_difference_at_fixed_point_in_time_test`,...
- new warning message when Cox models detects possible non-unique solutions to maximum likelihood.
- Generally: clean up lifelines exception handling. Ex: catch `LinAlgError: Matrix is singular.` and report back to the user advice.

- more bugs in `plot_covariate_groups` fixed when using non-numeric strata.