Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

AB test calculator run through Streamlit

Likelihood-Based Inference for Time Series Extremes

Code for ECE475: Frequentist Machine Learning at the Cooper Union, summer 2020

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Regression

A/B testing for KKBOX churn rate

A Python-based data analysis project using Jupyter Notebook, featuring classical and Bayesian inference methods applied to real-world datasets for statistical modeling, hypothesis testing, and portfolio optimization.