ExponentialFitter

class lifelines.fitters.exponential_fitter.ExponentialFitter(*args, **kwargs)

This class implements an Exponential model for univariate data. The model has parameterized form:

\[S(t) = \exp\left(\frac{-t}{\lambda}\right), \lambda >0\]

which implies the cumulative hazard rate is

\[H(t) = \frac{t}{\lambda}\]

and the hazard rate is:

\[h(t) = \frac{1}{\lambda}\]

After calling the .fit method, you have access to properties like: survival_function_, lambda_, cumulative_hazard_ A summary of the fit is available with the method print_summary()

Parameters:

alpha (float, optional (default=0.05)) – the level in the confidence intervals.

cumulative_hazard_

The estimated cumulative hazard (with custom timeline if provided)

Type:

DataFrame

confidence_interval_cumulative_hazard_

The lower and upper confidence intervals for the cumulative hazard

Type:

DataFrame

hazard_

The estimated hazard (with custom timeline if provided)

Type:

DataFrame

confidence_interval_hazard_

The lower and upper confidence intervals for the hazard

Type:

DataFrame

survival_function_

The estimated survival function (with custom timeline if provided)

Type:

DataFrame

confidence_interval_survival_function_

The lower and upper confidence intervals for the survival function

Type:

DataFrame

variance_matrix_

The variance matrix of the coefficients

Type:

DataFrame

median_survival_time_

The median time to event

Type:

float

lambda_

The fitted parameter in the model

Type:

float

durations

The durations provided

Type:

array

event_observed

The event_observed variable provided

Type:

array

timeline

The time line to use for plotting and indexing

Type:

array

entry

The entry array provided, or None

Type:

array or None

cumulative_density_

The estimated cumulative density function (with custom timeline if provided)

Type:

DataFrame

density_

The estimated density function (PDF) (with custom timeline if provided)

Type:

DataFrame

confidence_interval_cumulative_density_

The lower and upper confidence intervals for the cumulative density

Type:

DataFrame

percentile(p)

Return the unique time point, t, such that S(t) = p.

Parameters:

p (float)