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Table of Contents
Links
Causal Inference
Directed Acyclic Graphs
Markov-Chain Monte Carlo
Books
Statistical Rethinking
Videos
Richard McElreath
Miscellaneous
Python
R
Blogs
Links
Causal Inference
Directed Acyclic Graphs
Directed Acyclic Graphs (DAGs) – Libby Daniells
Markov-Chain Monte Carlo
Variance Reduction in Monte Carlo Methods: Importance Sampling - HackMD
Variance Reduction in Monte Carlo Methods: Self-Normalised Importance Sampling - HackMD
Books
Statistical Rethinking | Richard McElreath
Think Bayes 2 | Allen Downey
(
my fork
).
Bayes Rules! An Introduction to Bayesian Modeling with R
Bayesian Statistics - Syllabus
Gaussian Processes for Machine Learning
Statistical Rethinking
Statistical Rethinking course winter 2022
Statistical rethinking with brms, ggplot2, and the tidyverse: Second edition
Rethinking2 using Stan, R, rstan, tidybayes, and ggplot2
PyMC3 Rethinking 2
University of Bayes (Discord)
reading group for working through the book (
Fall 2022
).
Videos
An introduction to Markov Chain Monte Carlo using PyMC3
Richard McElreath
Statistical Rethinking (2023)
Statistical Rethinking (2019)
Bayesian Statistics without Frequentist Language
Science Before Statistics: Causal Inference
Miscellaneous
Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability)
Andrew Gelman et al. - Bayesian Workflow
Statistical Thinking (Frank Harrell) - Randomized Clinical Trials Do Not Mimic Clinical Practice, Thank Goodness
Python
PyMC3 Documentation — PyMC3 3.11.2 documentation
Pymc-Learn: Practical probabilistic machine learning in Python
BAyesian Model-Building Interface (Bambi) in Python — Bambi 0.5.0 documentation
PyStan — pystan 3.1.1 documentation
ArviZ: Exploratory analysis of Bayesian models — ArviZ dev documentation
R
bayesian
Blogs
Who would you rather date Bayes Factor or p-value?
