Lifelines

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.

New features
- Faster NPMLE for interval censored data
- New weightings available in the `logrank_test`: `wilcoxon`, `tarone-ware`, `peto`, `fleming-harrington`. Thanks sean-reed
- new interval censored dataset: `lifelines.datasets.load_mice`

Bug fixes
- Cleared up some mislabeling in `plot_loglogs`. Thanks sean-reed!
- tuples are now able to be used as input in univariate models.

New features
- Non parametric interval censoring is now available, _experimentally_. Not all edge cases are fully checked, and some features are missing. Try it under `KaplanMeierFitter.fit_interval_censoring`