Lifelines

Bug fixes
- fixed an edge case in `KaplanMeierFitter` where a really late entry would occur after all other population had died.
- fixed `plot` in `BreslowFlemingtonHarrisFitter`
- fixed bug where using `conditional_after` and `times` in `CoxPHFitter("spline")` prediction methods would be ignored.

Bug fixes
- fixed a bug where using `conditional_after` and `times` in prediction methods would result in a shape error
- fixed a bug where `score` was not able to be used in splined `CoxPHFitter`
- fixed a bug where some columns would not be displayed in `print_summary`

Bug fixes
- fixed a bug where `CoxPHFitter` would ignore inputed `alpha` levels for confidence intervals
- fixed a bug where `CoxPHFitter` would fail with working with `sklearn_adapter`

New features
- improved convergence of `GeneralizedGamma(Regression)Fitter`.

New features
- new spline regression model `CRCSplineFitter` based on the paper "A flexible parametric accelerated failure time model" by Michael J. Crowther, Patrick Royston, Mark Clements.
- new survival probability calibration tool `lifelines.calibration.survival_probability_calibration` to help validate regression models. Based on “Graphical calibration curves and the integrated calibration index (ICI) for survival models” by P. Austin, F. Harrell, and D. van Klaveren.

API Changes
- (and bug fix) scalar parameters in regression models were not being penalized by `penalizer` - we now penalizing everything except intercept terms in linear relationships.

New features
- New improvements when using splines model in CoxPHFitter - it should offer much better prediction and baseline-hazard estimation, including extrapolation and interpolation.

API Changes
- Related to above: the fitted spline parameters are now available in the `.summary` and `.print_summary` methods.

Bug fixes
- fixed a bug in initialization of some interval-censoring models -> better convergence.