From Math to Code: Building GAM with Penalty Functions From Scratch
Enjoyed learning penalized GAM math. Built penalty matrices, optimized λ using GCV, and implement our own GAM function. Confusing? Yes! Rewarding? Oh yes!
From Complete Separation To Maximum Likelihood Estimation in Logistic Regresion: A Note To Myself
Refreshed my rusty calculus skills lately! 🤓 Finally understand what happens during complete separation and why those coefficient SE get so extreme. The math behind maximum likelihood estimation makes more sense now! Chain rule, quotient rule, matrix inversion are crucial!
Exploring Non-linear Effects: Visual CATE Analysis of Continuous Confounders, Binary Exposures, and Continuous Outcomes
It was enjoyable to visualize the non-linear relationship with interaction and observe the corresponding changes in CATE. If one understands the underlying equation, it’s possible to easily obtain the ATE using calculus. Lastly, adopting Richard McElreath’s Owl framework as a documented procedure ensures quality assurance! 🙌