Skip to main content

statsim

StatSim — probabilistic programming and statistical computing for Python.

Install

# Basic installation
pip install statsim

# With PyMC backend
pip install statsim[pymc]

# With Stan backend
pip install statsim[stan]

# With all backends
pip install statsim[all]

Usage

from statsim import compile, run

# Compile .sm model
model = compile('''
  mu ~ Normal(0, 10)
  sigma ~ HalfNormal(5)
  y ~ Normal(mu, sigma)
''', target='pymc')

# Run inference
result = run(model, backend='pymc')

Backends

  • PyMC: Full Bayesian inference with MCMC and variational methods
  • Stan: High-performance HMC/NUTS sampling

Learn more

Metadata

Release files for statsim 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for statsim 0.1.0
File Size Uploaded Provenance Actions
statsim-0.1.0.tar.gz 3.0 kB Without provenance Details for statsim-0.1.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for statsim 0.1.0
File Interpreter ABI Platform Actions
statsim-0.1.0-py3-none-any.whl Python 3 none any Details for statsim-0.1.0-py3-none-any.whl

Total release size: 6.8 kB

Release files / statsim-0.1.0.tar.gz

Download URL statsim-0.1.0.tar.gz
Size 3.0 kB
Tags Source
SHA-256 checksum
How to use checksums
2760083c8619c5cb546efd89135255b1fd7bf05ab074c5a18b3a6d67df865829
BLAKE2b-256 checksum
How to use checksums
4e58df45320c84c68355c432600b4c17464dd626546d58dddc53ad9fa601a595
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Release files / statsim-0.1.0-py3-none-any.whl

Download URL statsim-0.1.0-py3-none-any.whl
Size 3.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
32ac89daa82ba76fba22774ed58bb0df51203dc048701e2a42fbe6213d9ab260
BLAKE2b-256 checksum
How to use checksums
f4c2bf0ef782c853101ab3839138d6d4551d876ee13a9ed08dffe4bfd722ea95
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.12

Security for statsim 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page