Oskar Laverny
I am currently an associate professor in statistics in Marseille (France). Actuary by formation, I focus my researches on high dimensional statistics and dependence structures estimations, with a lot of applications in insurance, reinsurance, and more recently public health. I do have a taste for numerical code and open-source software, and most of my work is freely available on GitHub.
Session
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 coefficients. Our first implementation, using an off-the-shelf numerical solver, was correct but very slow compared to competition. We describe here the step-by-step procedure to performance that led us to our current top-of-the-line implementation.