Skip to main content
Help us improve PyPI by participating in user testing. All experience levels needed!

statistical causality discovery based on cyclic model

Project description

cyclicmodel

Statistical causal discovery based on cyclic model.
This project is under development.

Summary

Python package that performs statistical causal discovery under the following condition:

  1. there are unobserved common factors
  2. two-way causal relationship exists

cyclicmodel has been developed based on bmlingam, which implemented bayesian mixed LiNGAM.

Example

import numpy as np
import pymc3 as pm
import cyclicmodel as cym

# Generate synthetic data,
# which assumes causal relation from x1 to x2
n = 200
x1 = np.random.randn(n)
x2 = x1 + np.random.uniform(low=-0.5, high=0.5, size=n)
xs = np.vstack([x1, x2]).T

# Model settings
hyper_params = cym.define_model.CyclicModelParams(
    dist_std_noise='log_normal',
    df_indvdl=8.0,
    dist_l_cov_21='uniform, -0.9, 0.9',
    dist_scale_indvdl='uniform, 0.1, 1.0',
    dist_beta_noise='uniform, 0.5, 6.0')

# Generate PyMC3 model
model = cym.define_model.get_pm3_model(xs, hyper_params, verbose=10)

# Run variational inference with PyMC3
with model:
  fit = pm.FullRankADVI().fit(n=100000)
  trace = fit.sample(1000, include_transformed=True)

# Check the posterior mean of the coefficients
print(np.mean(trace['b_21']))  # from x1 to x2
print(np.mean(trace['b_12']))  # from x2 to x1

Installation

pip install cyclicmodel

References

Project details


Release history Release notifications

This version
History Node

0.0.4

History Node

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
cyclicmodel-0.0.4-py3-none-any.whl (5.6 kB) Copy SHA256 hash SHA256 Wheel py3 Jun 14, 2018
cyclicmodel-0.0.4.tar.gz (5.4 kB) Copy SHA256 hash SHA256 Source None Jun 14, 2018

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging CloudAMQP CloudAMQP RabbitMQ AWS AWS Cloud computing Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page