Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Bayesian Statistics | 1 |
| Computation | 1 |
| Computer Software | 1 |
| Maximum Likelihood Statistics | 1 |
| Monte Carlo Methods | 1 |
| Probability | 1 |
| Programming Languages | 1 |
| Statistical Distributions | 1 |
| Statistical Inference | 1 |
Source
| Grantee Submission | 1 |
Author
| Betancourt, Michael | 1 |
| Brubaker, Marcus A. | 1 |
| Carpenter, Bob | 1 |
| Gelman, Andrew | 1 |
| Goodrich, Ben | 1 |
| Guo, Jiqiang | 1 |
| Hoffman, Matthew D. | 1 |
| Lee, Daniel | 1 |
| Li, Peter | 1 |
| Riddell, Allen | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkCarpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; Lee, Daniel; Goodrich, Ben; Betancourt, Michael; Brubaker, Marcus A.; Guo, Jiqiang; Li, Peter; Riddell, Allen – Grantee Submission, 2017
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…
Descriptors: Programming Languages, Probability, Bayesian Statistics, Monte Carlo Methods
