Causal models in Python
Project description
causalmodels in Python.
instalation
$ pip install causalmodels
usage
>>> import numpy as np >>> import causalmodels as cm >>> a = np.random.laplace(size=500) >>> b = np.random.laplace(size=500) + a >>> c = np.random.laplace(size=500) + a + b >>> data = np.array([c, b, a]) >>> >>> model = cm.DirectLiNGAM() >>> results = model.fit(data) >>> results.order [2, 1, 0] >>> result.draw()
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
causalmodels-0.1.6.tar.gz
(3.8 kB
view hashes)
Built Distribution
Close
Hashes for causalmodels-0.1.6-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5f98f37f6823e654e057529d90fbc17f0b6f7e66769ba5c8c029c116d9e27eed |
|
MD5 | f97355db32a2d6240e26082b0dfd02d8 |
|
BLAKE2b-256 | 6d067094b36786a91d8af5b231ba331e3474ffb9b86e1d74d7dd30d67625a381 |