Skip to main content

An implementation of Linear Mixed Model, a statistical model that promotes sparse variable selection in the presence of correlated and linearly dependent variables.

Project description

The author of this package has not provided a project description

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

sparse_lmm-1.0.1.tar.gz (132.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sparse_lmm-1.0.1-py3-none-any.whl (10.0 kB view details)

Uploaded Python 3

File details

Details for the file sparse_lmm-1.0.1.tar.gz.

File metadata

  • Download URL: sparse_lmm-1.0.1.tar.gz
  • Upload date:
  • Size: 132.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.16

File hashes

Hashes for sparse_lmm-1.0.1.tar.gz
Algorithm Hash digest
SHA256 7426369a43be14da3f7ada4b3d83d6d3331264c731063538e0cfd76a45f44dcb
MD5 d762f80fabb1c7fab8f9bac9c7669903
BLAKE2b-256 8b5cb815144424461f148b3306c1454339885910845ccc908e5184461b413392

See more details on using hashes here.

File details

Details for the file sparse_lmm-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: sparse_lmm-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 10.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.16

File hashes

Hashes for sparse_lmm-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 23ddda8485d550c93b69429ec1546ed4b297fa91c1e52ef80db328be007f62ca
MD5 aa39b41bbb5487bbb4d945d083da5221
BLAKE2b-256 67856c31f1afd78c4d0a3c68c9079b538aa17469b29406855e3b8257746fe7e7

See more details on using hashes here.

Supported by

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