framework for estimating small probabilities using MCMC based on PyMC3-like probability model
Project description
small_probs
This is the framework for estimation of small probabilities!
Getting started
Install from pip
First, we need pymc3_ext:
pip install git+https://github.com/wlad111/pymc3.git
Then install small_probs
with pip
:
pip install git+https://github.com/wlad111/small_probs.git
Running examples
After installation, example notebooks from small_probs/notebooks
are available
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for small_probs-wlad111-0.2.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | e1f865c7b0c353a4efabf50177ba08a802682c3f87bbcf28de40831fd28ce921 |
|
MD5 | 5f51fb2ccf08c22993fad8d112d79e01 |
|
BLAKE2b-256 | 41399be30767473d3fe2aee00105749cacde503c4e0777348af01abe2971e19f |
Close
Hashes for small_probs_wlad111-0.2.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 69845729959f0a1709e3c50437c7a3a3f6f1ee95a26b4e3fb79bf2e154eb9689 |
|
MD5 | 078ca17a13452f97cecca79ee3fd1bff |
|
BLAKE2b-256 | d300c0f6b363d51792f8cb8ab673be09c03d456148f02919a7fe612e7eb63205 |