This project contains a set of tutorials on how to perform descriptive and inferential (Bayesian and Frequentist) discrete-time event history analysis (EHA; a.k.a. hazard analysis, survial analysis, ...

当大多数成功学在教导如何复制赢家路径时，鹿白River的《自我迭代与AI时代》提供的是如何不成为输家的保底算法——这对资源有限、又身处AI技术颠覆浪潮中的普通人而言，往往更为实用。它跳出了传统成功学的线性叙事，将自我迭代与AI时代的不确定性深度绑定， ...

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...