Stan is a state-of-the-art platform for statistical modelling and high-performance statistical computation.

Here you will find tutorials on building statistical models and bayesian inference using Stan. Our goal is to help you familiarise yourself with the capabilities of the Stan language and how they can be applied to your own problems.

New videos uploaded regularly! Subscribe to never miss a tutorial!

Help us continue maintenance and development of Stan by making a small donation:
https://mc-stan.org/support

Efficient Hierarchical Gaussian Process Regression (Adam Gorm Hoffmann)
15:20
Efficient Hierarchical Gaussian Process Regression (Adam Gorm Hoffmann)
Nutpie: Fast and Efficient Bayesian Inference with Rust and Python (Adrian Seyboldt)
16:22
Nutpie: Fast and Efficient Bayesian Inference with Rust and Python (Adrian Seyboldt)
Joint estimation of body and tail loss development factors in insurance (Conor Goold)
19:03
Joint estimation of body and tail loss development factors in insurance (Conor Goold)
Sharing the Spotlight: How Artist Collaboration affects Song Popularity (Ethan Budge)
19:52
Sharing the Spotlight: How Artist Collaboration affects Song Popularity (Ethan Budge)
Generative Bayesian Modeling with Implicit Priors (Paul Buerkner)
20:30
Generative Bayesian Modeling with Implicit Priors (Paul Buerkner)
Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction ... (Jonas Mikhaeil)
17:54
Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction ... (Jonas Mikhaeil)
Psychological heterogeneity with Bayesian hierarchical models using the brms R package (Matti Vuore)
17:17
Psychological heterogeneity with Bayesian hierarchical models using the brms R package (Matti Vuore)
Applied modeling for drug development (Sebastian Weber)
1:03:24
Applied modeling for drug development (Sebastian Weber)
From the Depths to the Stars: Modeling Shark Movements (Vianey Leos Barajas)
54:55
From the Depths to the Stars: Modeling Shark Movements (Vianey Leos Barajas)
dynamite: An R Package for Dynamic Multivariate Panel Models (Jouni Helske)
13:35
dynamite: An R Package for Dynamic Multivariate Panel Models (Jouni Helske)
New fast heavy-tail count models in Stan (Zhi Ling)
18:44
New fast heavy-tail count models in Stan (Zhi Ling)
Structured Correlation Matrices (Sean Pinkney)
19:10
Structured Correlation Matrices (Sean Pinkney)
Bayesian inference for the analysis of blue whale movement data (Marco Antonio Gallegos Herrada)
22:00
Bayesian inference for the analysis of blue whale movement data (Marco Antonio Gallegos Herrada)
Copulas in Stan: Modeling Spatial Dependence ... (Brynjolfur Gauti Guorunar Johnsson)
17:07
Copulas in Stan: Modeling Spatial Dependence ... (Brynjolfur Gauti Guorunar Johnsson)
What’s your favorite sushi? Combining ranking and rating models in Stan (Bob Carpenter)
17:43
What’s your favorite sushi? Combining ranking and rating models in Stan (Bob Carpenter)
Inferring Personalized Diet Recommendations Using a Conditional Mixture... (Jari Turkia)
17:34
Inferring Personalized Diet Recommendations Using a Conditional Mixture... (Jari Turkia)
Priors, Posteriors, and Office Politics: Implementing Bayesian Workflow... (Jesse Piburn)
20:20
Priors, Posteriors, and Office Politics: Implementing Bayesian Workflow... (Jesse Piburn)
Integrating Bayesian Inference and System Dynamics with Case Studies in Epidemiology (Angie Moon)
22:12
Integrating Bayesian Inference and System Dynamics with Case Studies in Epidemiology (Angie Moon)
Advancing functional genomics analysis with Stan (Laura Jenniches)
22:38
Advancing functional genomics analysis with Stan (Laura Jenniches)
Running Multiple Short MCMC Chains on a GPU Using JAX for Fast Inference with Stan (Simon Maskell)
19:30
Running Multiple Short MCMC Chains on a GPU Using JAX for Fast Inference with Stan (Simon Maskell)
Collaborative Translation: Advancing the Stan Chinese Documentation (Ziyuan Zhang)
19:42
Collaborative Translation: Advancing the Stan Chinese Documentation (Ziyuan Zhang)
Efficiently estimating latent class (and standard) multivariate probit models (Enzo Cerullo)
16:48
Efficiently estimating latent class (and standard) multivariate probit models (Enzo Cerullo)
Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis (Anne Riha)
18:37
Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis (Anne Riha)
Bayesian Gaussian processes with correlated group effects (Gabriel Riutort Mayol)
16:44
Bayesian Gaussian processes with correlated group effects (Gabriel Riutort Mayol)
The Pragmatic Probabilistic Programmer (Mitzi Morris)
56:47
The Pragmatic Probabilistic Programmer (Mitzi Morris)
The use of Bayesian Hierarchical Modelling using simulated data (Charlotte Wilhelm-Benartzi)
23:44
The use of Bayesian Hierarchical Modelling using simulated data (Charlotte Wilhelm-Benartzi)
The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions (David Kohns)
20:09
The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions (David Kohns)
Bayesian workflow for time-varying transmission in stratified compartmental... (Judith Bouman)
19:24
Bayesian workflow for time-varying transmission in stratified compartmental... (Judith Bouman)
A Semi-Mechanistic Longitudinal Gaussian Process Regression Model... (Jacqueline Buros)
23:22
A Semi-Mechanistic Longitudinal Gaussian Process Regression Model... (Jacqueline Buros)
Bayesian Identification, Estimation, and Diagnostic for Growth Mixture Models (Xingyao Xiao)
18:59
Bayesian Identification, Estimation, and Diagnostic for Growth Mixture Models (Xingyao Xiao)