relife.parametric.ParametricHazardFunctions
relife.parametric.ParametricHazardFunctions¶
- class relife.parametric.ParametricHazardFunctions[source]¶
Bases:
relife.model.HazardFunctionsGeneric parametric hazard functions.
Generic class for the parametric hazard functions with a fitting method based on the maximum likelihood estimator.
Methods
Cumulative hazard function.
Hazard function (or hazard rate).
Inverse cumulative hazard function.
Attributes
Number of parameters.
Parameters of the hazard functions.
- abstract property params: numpy.ndarray¶
Parameters of the hazard functions.
- abstract property n_params: int¶
Number of parameters.
- chf(t: numpy.ndarray, *args: numpy.ndarray) numpy.ndarray[source]¶
Cumulative hazard function.
The cumulative hazard function is the integral of the hazard function.
- Parameters
t (float or 1D array) – Elapsed time.
*args (float or 2D array, optional) – Extra arguments required by the hazard function.
- Returns
Cumulative hazard function at t.
- Return type
float or ndarray
Notes
If args are of type ndarray, the arrays should be broadcastable with
shape[-1]=1.The shape of the result will be:
np.broadcast_shapes(*(np.shape(arg) for arg in args))[:-1] + (np.size(t),)
- hf(t: numpy.ndarray, *args: numpy.ndarray) numpy.ndarray[source]¶
Hazard function (or hazard rate).
The hazard function is the derivative of the cumulative hazard function.
- Parameters
t (float or 1D array) – Elapsed time.
*args (float or 2D array, optional) – Extra arguments required by the hazard function.
- Returns
Hazard rate at t.
- Return type
float or 1D array
Notes
If args are of type ndarray, the arrays should be broadcastable with
shape[-1]=1.The shape of the result will be:
np.broadcast_shapes(*(np.shape(arg) for arg in args))[:-1] + (np.size(t),)
- ichf(v: numpy.ndarray, *args: numpy.ndarray) numpy.ndarray[source]¶
Inverse cumulative hazard function.
- Parameters
v (float or 1D array) – Cumulative hazard rate
*args (float or 2D array, optional) – Extra arguments required by the hazard function.
- Return type
float or ndarray
Notes
If args are of type ndarray, the arrays should be broadcastable with
shape[-1]=1.The shape of the result will be:
np.broadcast_shapes(*(np.shape(arg) for arg in args))[:-1] + (np.size(t),)