A survival guide to survival analysis- ongoing mathematical blog series
After getting a bit tired of the constant stream of agentic AI/vibe-coding/context engineering/harness engineering content, I started to move into some relatively lesser explored areas in statistics- that's how I stumbled into survival analysis.
This is an ongoing blog series built from first principles. The emphasis is on actual mathematics of time-to-event modeling. It's not a "5-minute intro to survival analysis" or "Learn time-to-event modeling in 10 days using Python and lifelines".
If you like mathematical explanations, you may actually enjoy it.
Here's the series link- Articles – Madhav’s Blog
Here's one part- Part 3: Fitting Survival Distributions to Data – Madhav’s Blog
I am open to feedback and suggestions.
Disclaimer: I used Claude and ChatGPT for structuring/editing/proof-reading; the core ideas are mine.