Skip to main content

Plotting code to visualize models estimated with the mssm toolbox.

Project description

mssmViz

Docs

Description

Plotting functions for the Mixed Sparse Smooth Models (mssm) toolbox. mssm is a toolbox to estimate Generalized Additive Mixed Models (GAMMs), Generalized Additive Mixed Models of Location Scale and Shape (GAMMLSS), and even more general smooth models in the sense defined by Wood, Pya, & Säfken (2016). In addition, a tutorial for mssm is provided with this repository. Documentation for mssmViz is hosted here.

Installation

To install mssm simply run:

conda create -n mssm_env python=3.11
conda activate mssm_env
pip install mssm

Subsequently, mssmViz can be installed by running:

pip install mssmViz

Alternatively, you can clone the repository into a folder of your choice:

git clone https://github.com/JoKra1/mssm_tutorials.git

After navigating to the folder into which you cloned this repository, you can then install mssmViz plot functions by running:

pip install -e .

The -e flag will ensure that any new changes you pull from this repository will be reflected when you use the plot functions.

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

mssmviz-0.1.46.tar.gz (3.5 MB view details)

Uploaded Source

Built Distribution

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

mssmviz-0.1.46-py3-none-any.whl (38.4 kB view details)

Uploaded Python 3

File details

Details for the file mssmviz-0.1.46.tar.gz.

File metadata

  • Download URL: mssmviz-0.1.46.tar.gz
  • Upload date:
  • Size: 3.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mssmviz-0.1.46.tar.gz
Algorithm Hash digest
SHA256 094a0a6cbb7113a27bb2b3856a3bce2e5e89eeca8e0853bbef5e82a4c5e28652
MD5 bf0d6bb113e3c43ef1d3df9e686359cf
BLAKE2b-256 d8337bd5400df5efa74844464d06076b7735460043bd269c66863b4791a95642

See more details on using hashes here.

Provenance

The following attestation bundles were made for mssmviz-0.1.46.tar.gz:

Publisher: python-package.yml on JoKra1/mssm_tutorials

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mssmviz-0.1.46-py3-none-any.whl.

File metadata

  • Download URL: mssmviz-0.1.46-py3-none-any.whl
  • Upload date:
  • Size: 38.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mssmviz-0.1.46-py3-none-any.whl
Algorithm Hash digest
SHA256 9f95cb659a6194843c30b6b32d16743afc0a5243131de2f3a2540acb4cf0d12d
MD5 342a0d23be22fcf8a6c389168a8c4b31
BLAKE2b-256 d18264ff53c2f0fc2447633bebe2e177be835b8250e1d12d6f8b171b6b577599

See more details on using hashes here.

Provenance

The following attestation bundles were made for mssmviz-0.1.46-py3-none-any.whl:

Publisher: python-package.yml on JoKra1/mssm_tutorials

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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