stan-dev / cmdstanpyLinks
CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.
☆191Updated last month
Alternatives and similar repositories for cmdstanpy
Users that are interested in cmdstanpy are comparing it to the libraries listed below
Sorting:
- Exploring and eliciting probability distributions☆162Updated last month
- Python wrapper for nuts-rs☆188Updated this week
- Database with posteriors of interest for Bayesian inference☆212Updated this week
- Powerful add-ons for PyMC☆133Updated this week
- Bayesian Regression Models in Pyro☆74Updated last year
- Simulation based calibration and generation of synthetic data.☆56Updated 2 months ago
- ☆135Updated last week
- Formulas for mixed-effects models in Python☆64Updated 3 weeks ago
- ☆18Updated 3 years ago
- Inference case studies in knitr☆171Updated 3 years ago
- Bayesian Conjugate Models in Python☆37Updated last week
- Educational resources☆105Updated 4 years ago
- ☆73Updated 7 years ago
- Source repository for the online book Exploratory Analysis of Bayesian Models.☆25Updated this week
- Stan models for state space time series☆146Updated 8 years ago
- PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io☆358Updated last year
- Bayesian inference and posterior analysis for Python☆46Updated 2 years ago
- Inference case studies in jupyter☆93Updated 7 years ago
- CmdStan, the command line interface to Stan☆237Updated last week
- Source files for the book "Bayesian Workflow Using Stan"☆97Updated 4 years ago
- Kullback-Leibler projections for Bayesian model selection in Python☆40Updated last month
- Markov chain Monte Carlo general, and Hamiltonian Monte Carlo specific, diagnostics for Stan☆89Updated 3 weeks ago
- ArviZ modular plotting☆19Updated this week
- BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.☆110Updated 3 weeks ago
- ☆57Updated 3 years ago
- Randomization-based inference in Python☆84Updated last week
- Random Forests for Conditional Density Estimation☆43Updated 4 years ago
- Hidden Markov models in PyMC3☆96Updated last year
- A Beginner's Guide to Variational Inference☆18Updated 9 months ago
- Compares Stan, PyMC, and PyMC + JAX numpyro sampler on a model for tennis☆33Updated 3 years ago