julia

Cox model go brrr: a journey to performance

The Cox model is a standard and very well studied parametric model for censored time-to-event data, relying on very strict proportional hazard assumptions. It is one of the core tools of survival analysis and requires numerical estimation of its …

Non-parametric estimation of net survival under dependence between death causes

Non-parametric estimation of net survival under dependence between death causes

Non-parametric estimation of net survival under dependence between death causes

Relative survival methodology deals with a competing risks survival model where the cause of death is unknown. This lack of information occurs regularly in population-based cancer studies. Non-parametric estimation of the net survival is possible …

NetSurvival.jl: A glimpse into relative survival analysis with Julia

In many population-based medical studies, the specific cause of death is unidentified, unreliable or even unavailable. Relative survival analysis addresses this scenario, outside of standard (competing risks) survival analysis, to nevertheless …

NetSurvival.jl: A glimpse into relative survival analysis

Shine of multiple dispatch: the `Copulas.jl` case.

Julia: the unique solution to an optimisation problem

Copulas.j: A fully Distribution.jl-complient copula package

Estimation and sampling of copulas in Julia with Copulas.jl

Announce I am proud to annonce the publication and the registration of my new Julia package, Copulas.jl. As it’s name suggests, Copulas.jl is a package that implements methods and tools to work with an arround copulas in the Julia programming language.