Resumen
Survival Analysis is a broad and crucial field of Statistical Science.
Survival models are useful for estimating the reliability function, describe data properties and more.
Considering medical studies, the aim is studying the time until an event occurs, like the death
of a patient.
However, there can be situations in which the subject will not experience
the event. In this study, we explore two parametric models for modelling the cure rate,
the mixture model and the defective model.
The times to event are assumed to follow the Gompertz distribution.
Both frequentist and Bayesian approaches are considered for
the estimation problem.
To exemplify the discussed theory, applications in real data are discussed.