Skip to main content

A small package for causal inference in spatial cross-sectional data

Project description

gccm

This is a package designed for causal inference in spatial cross-sectional data. This Python package is a conversion of the R language code provided in the article "Causal inference from cross-sectional earth system data with geographical convergent cross mapping", with some minor optimizations applied. You can see more details from https://github.com/spjace/gccm/ and https://www.nature.com/articles/s41467-023-41619-6

Project details


Download files

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

Source Distribution

gccm-0.0.0.tar.gz (2.0 kB view details)

Uploaded Source

File details

Details for the file gccm-0.0.0.tar.gz.

File metadata

  • Download URL: gccm-0.0.0.tar.gz
  • Upload date:
  • Size: 2.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.11

File hashes

Hashes for gccm-0.0.0.tar.gz
Algorithm Hash digest
SHA256 2094986a5afe8d72539d4bbadc68e0c629623bf10857e15cb37921f39d76fdf0
MD5 f1b8382156a534d5f9b6c13811e052dc
BLAKE2b-256 992f6e38804649480a644f9bfff9e5eea9fe2310e81acc8f41fbe444ae3f7d96

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page