### Slides for NY Open Statistical Programming Meetup

Introductory Survey of Bayesian Methods Considering Dynamic Linear Models(pdf), a talk given to the NY Open Statistical Programming Meetup on 16 March 2016.### Introductory

A primer in Bayesian Inference by Aart F. de VosIntroduction 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