Advanced Statistical Computing in the Age of AI

A graduate textbook in biostatistics

Welcome

This is the online version of Advanced Statistical Computing in the Age of AI by The rgtlab Curriculum Project, a graduate textbook in biostatistics.

The book is the second volume in a graduate sequence. It assumes the foundational material of the introductory companion volume, Statistical Computing in the Age of AI, and takes up the topics that build on that foundation: numerical stability and conditioning; numerical linear algebra in depth; advanced optimization; the EM algorithm and its extensions; Monte Carlo and MCMC in depth; modern Bayesian computation; high-performance and distributed computing; high-dimensional methods; machine learning for biostatistics; software engineering for statisticians; reproducible computational environments; and advanced interactive visualization.

A workflow companion volume, Biostatistics Practicum, covers the day-to-day infrastructure of reproducible biostatistical research (Git, Docker, renv, Quarto, CDISC, SAS) that surrounds the methods both volumes describe.

The reader is referred to the Preface for motivation and to the Conventions page for the visual cues used throughout.

License

This book is licensed to you under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The code samples in this book are licensed under Creative Commons CC0 1.0 Universal (CC0 1.0), i.e. public domain.