Slides for Kx Bayes(ic) Meetup
Introductory Survey of Bayesian Methods Considering Dynamic Linear Models(pdf), a talk given to the Kx Community NYC Meetup on January 23rd, 2020.Introductory
A primer in Bayesian Inference by Aart F. de VosPart 1 by Chris Bishop - Introduction to Bayesian Inference
Jaynes's "Probability Theory: The Logic of Science"
Unofficial Errata and Commentary [for the above]
Video lecture by Sharon McGrayne on her book "The Theory That Would Not Die"
What is Bayesian statistics and why everything else is wrong
General Bayesian
Bayesian Inference ResourcesConditional Probability: a visual explanation
Motivating the Bayesian prior with de Finetti's theorem
de Finetti was right: Probability does not exist
Bayesian Software
Bayesian Inference on A Binomial Proportion (R)The BUGS Project Graphical model software links
Open BUGS (Bayesian Inference Using Gibbs Sampling)
R2OpenBUGS: A Package for Running OpenBUGS from R
R packages used for Bayesian inference
Wolfram interactive CDF player
Bayesian Inference on a Binomial Proportion
Bayesian Networks
A Tutorial on Learning With Bayesian Networks by David Heckerman, March 1995 (tr-95-06.pdf)A Brief Introduction to Graphical Models and Bayesian Networks, by Kevin Murphy, 1998
Working Examples of Bayesian Networks
Boosted Learning in Dynamic Bayesian Networks for Multimodal Speaker Detection by Garg, Pavlovic, Rehg
Dynamic Linear Models
Bayesian Financial Dynamic Linear ModelDynamic Linear Models with R by Petris, et al.
Good working paper by Mike West
Introduction to Dynamic Linear Models
Time series and dynamic linear models
Gibbs Samplers, other MCMC-based Techniques
Hidden Markov Models in RMarkov Chain Monte Carlo and Applied Bayesian Statistics
Self-contained intro to the Metropolis-Hastings algorithm
Learning With Hidden Variables