Stan : A Probabilistic Programming Language
Columbia University · Creative Technologies (United States) · +3 more institutions
Abstract
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 No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as…
Citation impact
- FWCI
- 610.22
- Percentile
- 100%
- References
- 51
Authors
10Topics & keywords
- Python (programming language)
- Computer science
- Markov chain Monte Carlo
- Algorithm
- Hybrid Monte Carlo
- Monte Carlo method
- Probabilistic logic
- Bayesian inference