API

The content of the exposed ReLife API. It is where one can find details about object interfaces (how many parameters are needeed by a function, what are their types, etc.).

Lifetime models

Lifetime models are objects whose exposed interface can answer basic probility functions of the survival analysis. In object-oriented programming, one must not see them as a group of probability functions solely : it also encapsulates data like parameters, other nested models, etc.

Exponential	Exponential lifetime distribution.
Weibull	Weibull lifetime distribution.
Gompertz	Gompertz lifetime distribution.
Gamma	Gamma lifetime distribution.
LogLogistic	Log-logistic probability distribution.
ProportionalHazard	Proportional Hazard regression model.
AFT	Accelerated failure time regression.

Non-parametric lifetime estimators

Non-parametric lifetime estimators are objects used to compute well-knowns non-parametric estimations of some probability functions. Their exposed interface follows the same logic of lifetime models except that they do not store parameters but estimations of functions values.

ECDF	Empirical Cumulative Distribution Function.
KaplanMeier	Kaplan-Meier estimator.
NelsonAalen	Nelson-Aalen estimator.
Turnbull	Turnbull estimator

Renewal policies

Renewal policies are objects that are generally composed of one underlying renewal process and one or more lifetime model. Their interfaces expose a bunch of statiscal properties like expections and a sample procedure to generate data.

OneCycleAgeReplacementPolicy	One-cyle age replacement policy.
OneCycleRunToFailure	One cyle run-to-failure policy
RunToFailure	Run-to-failure renewal policy.
AgeReplacementPolicy	Time based replacement policy.

Likelihoods

likelihoods.LikelihoodFromLifetimes

Generic likelihood object for parametric lifetime models

Decorator models

A decorator model is basically a LifetimeModel object that wraps another LifetimeModel object set as a baseline. Those models mainly deserves to some functionnalities in Policy object but advanced users can clearly use them for a specific purpose. For instance LeftTruncatedModel wraps a baseline model by overriding some of its probibability function in order to take into account the time condition imposed by a left trunctation a0.

model.AgeReplacementModel	Age replacement model.
model.LeftTruncatedModel	Left truncated model.
model.EquilibriumDistribution	Equilibrium distribution.

Base class

What we call base class are objects (in Python class are objects) used at the core of ReLife subsystems. For beginners, it is not necessary to know them. If you start to inspect ReLife code, you will encounter them regularly in inheritance hierarchy. In fact, most objects created for fiability theory inherits from one of those objects. One can think of them as engines that empower objects with special functionalities to make ReLife model creation easier.

model.Parameters	Tree-structured parameters.
model.ParametricModel	Base class to create a parametric model.
model.LifetimeModel	Base class to create a lifetime model.
model.ParametricLifetimeModel	Base class to create a parametric lifetime model