STAT 207 Intermediate Bayesian Statistical Modeling

Zehang Richard Li, UCSC

Lecture Slides

Lecture 0 — Course IntroductionPDF ↓
Lecture 1 — Bayesian inference basicsPDF ↓
Lecture 2 — Multi-parameter modelsPDF ↓
Lecture 3 — Hierarchical modelsPDF ↓
Lecture 4 — MCMCPDF ↓
Lecture 5 — Missing dataPDF ↓
Lecture 6 — Finite mixture modelsPDF ↓
Lecture 7 — Regression and model checkingPDF ↓
Lecture 8 — Advanced regressionPDF ↓
Lecture 9 — Robust inferencePDF ↓
Lecture 10 — Modal approximationPDF ↓
Lecture 11 — Slice sampling and HMCPDF ↓
Lecture 12 — INLAPDF ↓

Homework

Homework 1PDF ↓
Homework 2PDF ↓
Homework 3PDF ↓
Homework 4PDF ↓

Take-Home Assignments

TH-1PDF ↓