FrozenParametricLifetimeModel#

class relife.lifetime_model.FrozenParametricLifetimeModel(model, *args)[source]#

Methods

cdf

The cumulative density function.

chf

The cumulative hazard function.

hf

The hazard function.

ichf

Inverse cumulative hazard function.

isf

The inverse survival function.

ls_integrate

Lebesgue-Stieltjes integration.

mean

The mean.

median

The median.

moment

n-th order moment.

mrl

The mean residual life function.

pdf

The probability density function.

ppf

The percent point function.

rvs

Random variable sampling.

sf

The survival function.

unfreeze

var

The variance.

cdf(time)[source]#

The cumulative density function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

chf(time)[source]#

The cumulative hazard function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

hf(time)[source]#

The hazard function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

ichf(cumulative_hazard_rate)[source]#

Inverse cumulative hazard function.

Parameters:
cumulative_hazard_ratefloat or np.ndarray

Cumulative hazard rate value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given probability value(s).

isf(probability)[source]#

The inverse survival function.

Parameters:
probabilityfloat or np.ndarray

Probability value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given probability value(s).

ls_integrate(func, a, b, deg=10)[source]#

Lebesgue-Stieltjes integration.

Parameters:
funccallable (in1 ndarray , out1 ndarray)

The callable must have only one ndarray object as argument and one ndarray object as output

andarray (maximum number of dimension is 2)

Lower bound(s) of integration.

bndarray (maximum number of dimension is 2)

Upper bound(s) of integration. If lower bound(s) is infinite, use np.inf as value.)

degint, default 10

Degree of the polynomials interpolation

Returns:
np.ndarray

Lebesgue-Stieltjes integral of func from a to b.

mean()[source]#

The mean.

Returns:
np.float64 or np.ndarray
median()[source]#

The median.

Returns:
np.float64 or np.ndarray
moment(n)[source]#

n-th order moment.

Parameters:
nint

Order of the moment (at least 1)

Returns:
np.float64 or np.ndarray
mrl(time)[source]#

The mean residual life function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

property nb_params#

Number of parameters.

Returns:
int

Number of parameters.

property params#

Parameters values.

Returns:
ndarray

Parameters values of the core

Notes

If parameter values are not set, they are encoded as np.nan value.

Parameters can be by manually setting`params` through its setter, fitting the core if fit exists or by specifying all parameters values when the core object is initialized.

property params_names#

Parameters names.

Returns:
list of str

Parameters names

Notes

Parameters values can be requested (a.k.a. get) by their name at instance level.

pdf(time)[source]#

The probability density function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

ppf(probability)[source]#

The percent point function.

Parameters:
probabilityfloat or np.ndarray

Probability value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given probability value(s).

rvs(size, return_event=False, return_entry=False, seed=None)[source]#

Random variable sampling.

Parameters:
sizeint, (int,) or (int, int)

Size of the generated sample. If size is n or (n,), n samples are generated. If size is (m,n), a 2d array of samples is generated.

return_eventbool, default is False

If True, returns event indicators along with the sample time values.

return_entrybool, default is False

If True, returns corresponding entry values of the sample time values.

seedoptional int, default is None

Random seed used to fix random sampling.

Returns:
float, ndarray or tuple of float or ndarray

The sample values. If either return_event or return_entry is True, returns a tuple containing the time values followed by event values, entry values or both.

sf(time)[source]#

The survival function.

Parameters:
timefloat or np.ndarray

Elapsed time value(s) at which to compute the function. If ndarray, allowed shapes are (), (n,) or (m, n).

Returns:
np.float64 or np.ndarray

Function values at each given time(s).

var()[source]#

The variance.

Returns:
np.float64 or np.ndarray