Skip to main content

A Python package for frailty-based multivariate survival data analysis with competing risks

Project description

PyFCR is a robust Python package used for survival estimation procedure under the multivariate normal frailty model. It accommodates any number of competing risks and diverse configurations.

Project details


Release history Release notifications | RSS feed

This version

1.3

Download files

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

Source Distribution

PyFCR-1.3.tar.gz (39.9 kB view details)

Uploaded Source

Built Distributions

PyFCR-1.3-cp311-cp311-macosx_14_0_arm64.whl (71.1 kB view details)

Uploaded CPython 3.11 macOS 14.0+ ARM64

PyFCR-1.3-cp310-cp310-win_amd64.whl (373.3 kB view details)

Uploaded CPython 3.10 Windows x86-64

File details

Details for the file PyFCR-1.3.tar.gz.

File metadata

  • Download URL: PyFCR-1.3.tar.gz
  • Upload date:
  • Size: 39.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for PyFCR-1.3.tar.gz
Algorithm Hash digest
SHA256 f0c86521956b95e4d3fc139533a7f899e9a31348fb5f66edca033f0aaf50d582
MD5 95b3ba3a6530388ae59853d9db753efb
BLAKE2b-256 c18227f885c70b85e8757fcac92499df671738094b202d6e03eb03919662475e

See more details on using hashes here.

File details

Details for the file PyFCR-1.3-cp311-cp311-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for PyFCR-1.3-cp311-cp311-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 7146dd8e3886886c7d99fdd365d5b13e33b1a2c4f212617684e1f1c18ddf1cdb
MD5 34ae33b962969c99b0bb2e0e7f016945
BLAKE2b-256 6afb233f3c0e7396e73dd0f07504bb80c4cc24bddde46a1948ffe8dcab15cdb3

See more details on using hashes here.

File details

Details for the file PyFCR-1.3-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyFCR-1.3-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 373.3 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for PyFCR-1.3-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 78a64651e83df8aa45e1421d637e6f190ba66d01b7b55dbe62e097c680a57739
MD5 b129971b78689ba2d04625f66e1f1b16
BLAKE2b-256 6b837652f986abac9be77899066b37db805e75394ab2fef2ce6c1771f39b8c36

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