Skip to main content

Uniform confidence bands with theoretical covering guarantees

Project description

📐 Uniform Bands

uniform_bands is a simple Python package providing a function that computes uniform confidence bands from initial high probability lower and upper bounds using either the uniform or student method, with theoretical covering guarantees.


✨ Features

  • Multiple Methods: Choose between "uniform" and "student" bands depending on the desired statistical properties.
  • Input Flexibility: Works with 2D or higher-dimensional arrays, supporting potentially different lower and upper bounds.

🚀 Installation

pip install uniformbands

📖 Learn More

For tutorials, API reference, visit the official site:
👉 uniformbands Documentation

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

uniformbands-0.1.1.tar.gz (15.9 kB view details)

Uploaded Source

Built Distribution

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

uniformbands-0.1.1-py3-none-any.whl (16.3 kB view details)

Uploaded Python 3

File details

Details for the file uniformbands-0.1.1.tar.gz.

File metadata

  • Download URL: uniformbands-0.1.1.tar.gz
  • Upload date:
  • Size: 15.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for uniformbands-0.1.1.tar.gz
Algorithm Hash digest
SHA256 a618ce4d1c1e9f3f1318c9edaa5086375812284830f09c85e6e139664f54ef00
MD5 ab31e48e39cde42b29a64a9e3416a045
BLAKE2b-256 8578c1e6ced7b952d523555109156b03659eded4b48ef57ce160813fbe785fdb

See more details on using hashes here.

File details

Details for the file uniformbands-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: uniformbands-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 16.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for uniformbands-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3d3332d53df976266b465cb1cbdb97469fa66ad4b5589043dd4d58d660296dd9
MD5 0be7ffb20fac5e56d887456b07061bf4
BLAKE2b-256 7643f7f4c56f90ed9d5a64f6b36b1264e7e541697dff258be94a413410ac1c7d

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