Introduction to Bayesian Analysis using Stan
Date:
29/04/2025 - 30/04/2025
Organised by:
Royal Statistical Society
Presenter:
Robert Grant
Level:
Intermediate (some prior knowledge)
Contact:
Description:
Level: Intermediate (I)
This two-day course is ideal for beginners or intermediate users of Bayesian modelling, who want to learn how to use Stan software within R (the material we cover can easily be applied to other Stan interfaces, such as Python or Julia). We will learn about constructing a Bayesian model in a flexible and transparent way, and the benefits of using a probabilistic programming language for this. The language in question, Stan, provides the fastest and most stable algorithms available today for fitting your model to your data. Participants will get lots of hands-on practice with real-life data, and lots of discussion time. We will also look at ways of validating, critiquing and improving your models.
Learning Outcome
- Use Stan to fit various models to data
- Check outputs for computational problems, and know what to do to fix them
- Compare and critique competing models
- Justify their modelling choices, including prior probability distributions
- Understand what Stan can and cannot do
Topics Covered
- A quick overview of Bayesian analysis
- Simulation is useful for statistical inference
- What is a probabilistic programming language?
- Parts of a Stan model
- Univariate models; exploring priors and likelihoods
- Prior predictive checking
- Bivariate regression models
- Predictions and posterior predictive checking
- Hierarchical models
- Latent variable models including item-response theory
- Working with missing and coarse data
- Gaussian processes
- Limitations of Stan
Target Audience
Anyone with some statistics training who is aware of the advantages of Bayesian modelling could benefit from attending. Fields where this may be most popular are: insurance, political pollsters, finance, marketing, healthcare, education research, psychology, econometrics.
Assumed Knowledge
Attendees should be comfortable with using R, Python, Julia or Stata. They should understand probability distributions and basic regression models, though this can be intuitive and doesn’t have to be mathematically rigorous. They do not need to have used Stan before.
Cost:
Prices from £687.60 to £954.00 (inc. VAT)
Website and registration:
Region:
Greater London
Keywords:
Quantitative Data Handling and Data Analysis, Bayesian,. Stan
Related publications and presentations from our eprints archive:
Quantitative Data Handling and Data Analysis