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GraphEM

Gaussian graphical models (aka Markov random fields) embedded within an Expectation Maximization algorithm

https://github.com/paleopresto/GraphEM

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 12 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.0%) to scientific vocabulary

Keywords

climate-field-reconstructions
Last synced: 11 months ago · JSON representation

Repository

Gaussian graphical models (aka Markov random fields) embedded within an Expectation Maximization algorithm

Basic Info
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 1
  • Open Issues: 3
  • Releases: 0
Topics
climate-field-reconstructions
Created about 5 years ago · Last pushed over 4 years ago
Metadata Files
Readme License

README.rst 

.. image:: https://img.shields.io/github/last-commit/paleopresto/GraphEM/main
    :target: https://github.com/paleopresto/GraphEM

.. image:: https://img.shields.io/github/license/paleopresto/GraphEM
    :target: https://github.com/paleopresto/GraphEM/blob/master/LICENSE

.. image:: https://img.shields.io/pypi/pyversions/GraphEM
    :target: https://pypi.org/project/GraphEM

.. image:: https://img.shields.io/pypi/v/GraphEM.svg
    :target: https://pypi.org/project/GraphEM

*******
GraphEM
*******

GraphEM refers to the climate field reconstruction approach proposed by `Guillot et al. (2015) `_, and its name means Gaussian graphical models embedded within an EM (Expectation-Maximization) algorithm.

Documentation
=============

+ Homepage: https://paleopresto.github.io/GraphEM
+ Installation: https://paleopresto.github.io/GraphEM/installation.html
+ Tutorial (html): https://paleopresto.github.io/GraphEM/tutorial.html
+ Tutorial (Jupyter notebooks): https://github.com/paleopresto/GraphEM/tree/master/docsrc/tutorial

Reference of the GraphEM algorithm
==================================

+ Guillot, D., Rajaratnam, B., & Emile-Geay, J. (2015). Statistical paleoclimate reconstructions via Markov random fields. The Annals of Applied Statistics, 9(1), 324–352. https://doi.org/10.1214/14-AOAS794

Published studies using GraphEM
===============================

+ Vaccaro, A., Emile-Geay, J., Guillot, D., Verna, R., Morice, C., Kennedy, J., & Rajaratnam, B. (2021). Climate field completion via Markov random fields – Application to the HadCRUT4.6 temperature dataset. Journal of Climate, 1(aop), 1–66. https://doi.org/10.1175/JCLI-D-19-0814.1
+ Neukom, R., Steiger, N., Gómez-Navarro, J. J., Wang, J., & Werner, J. P. (2019). No evidence for globally coherent warm and cold periods over the preindustrial Common Era. Nature, 571(7766), 550–554. https://doi.org/10.1038/s41586-019-1401-2
+ Wang, Jianghao, Emile-Geay, J., Guillot, D., McKay, N. P., & Rajaratnam, B. (2015). Fragility of reconstructed temperature patterns over the Common Era: Implications for model evaluation. Geophysical Research Letters, 42(17), 7162–7170. https://doi.org/10.1002/2015GL065265
+ Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J. E., & Rajaratnam, B. (2014). Evaluating climate field reconstruction techniques using improved emulations of real-world conditions. Clim. Past, 10(1), 1–19. https://doi.org/10.5194/cp-10-1-2014

Owner

  • Name: Paleoclimate Reconstruction Storehouse
  • Login: paleopresto
  • Kind: organization

GitHub Events

Total
Last Year

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 37
  • Total Committers: 3
  • Avg Commits per committer: 12.333
  • Development Distribution Score (DDS): 0.054
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Feng Zhu f****e@o****m 35
CommonClimate j****g@u****u 1
Julien Emile-Geay C****e 1
Committer Domains (Top 20 + Academic)
usc.edu: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 3
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • CommonClimate (3)
Pull Request Authors
Top Labels
Issue Labels
enhancement (1)
Pull Request Labels

Dependencies

setup.py pypi
  • LMRt *