CRCSplineFitter¶
- class lifelines.fitters.crc_spline_fitter.CRCSplineFitter(n_baseline_knots: int | None = None, knots: list | None = None, *args, **kwargs)¶
Below is an implementation of Crowther, Royston, Clements AFT cubic spline models. Internally, lifelines uses this for survival model probability calibration, but it can also be useful for a highly flexible AFT model.
- Parameters:
n_baseline_knots (int) – the number of knots in the cubic spline.
References
Crowther MJ, Royston P, Clements M. A flexible parametric accelerated failure time model.
Examples
from lifelines import datasets, CRCSplineFitter rossi = datasets.load_rossi() regressors = {"beta_": "age + C(fin)", "gamma0_": "1", "gamma1_": "1", "gamma2_": "1"} crc = CRCSplineFitter(n_baseline_knots=3).fit(rossi, "week", "arrest", regressors=regressors) crc.print_summary()
- fit_intercept = True¶
- set_knots(T, E)¶