Examples of working and non-working models, initially for ODCS 2016 in Boston.
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LICENSE
README.md
donut-sim-corrected.stan
donut-sim.R
donut-sim.stan
m1-simulate-normal.stan
m2-estimate-normal.stan
m3-simulate-batches.stan
m4-estimate-batches.stan
m5-estimate-hierarchy.stan
m6-estimate-nc-hierarchy.stan
m7-estimate-nc-t-hierarchy.stan
odsc-1-mini-simulation-study.R
odsc-10-quantile-estimation.R
odsc-2-batch-simulation.R
odsc-3-batch-model.R
odsc-4-hierarchy-model.R
odsc-5-nc-hierarchical-model.R
odsc-6-nc-t-hierarchical-model.R
odsc-7-slacking-simulation.R
odsc-8-slacking-model.R
odsc-9-slacking-fix.R

README.md

stan-workshop

Examples of working and non-working models, initially for ODCS 2016 in Boston.

To make the best use of your time at the workshop, please look over the scripts in this repo and:

Install Stan

Installing Stan is straightforward. Installation instructions are interface language and platform specific and can be found here. Our examples will be done using R, but you should be able to follow along if you are using other languages like Python or Julia.

Download a Copy of the Stan Manual

Stan manual is full of usefull information and is part Bayesian textbook, part language reference. In particular, take a look at Section 3, Page 34 -- Data Types.

If You Are New to Bayes

If you are not familiar with the Bayesian paradigm, we will do a (very) quick introduction at the beginning of the workshop, but not enough to make people who had never seen Bayes comfortable with the subject. For those people, we recommend: