Metadata-Version: 2.1
Name: GraphEM
Version: 0.0.9
Summary: Gaussian Markov random ﬁelds embedded within an EM algorithm
Home-page: https://github.com/fzhu2e/GraphEM
Author: Feng Zhu, Dominique Guillot, Julien Emile-Geay
Author-email: fengzhu@usc.edu, dguillot@udel.edu, julieneg@usc.edu
License: MIT license
Description: .. image:: https://img.shields.io/github/last-commit/fzhu2e/GraphEM/master
            :target: https://github.com/fzhu2e/GraphEM
        
        .. image:: https://img.shields.io/github/license/fzhu2e/GraphEM
            :target: https://github.com/fzhu2e/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) <https://doi.org/10.1214/14-AOAS794>`_, and its name means Gaussian Markov random ﬁelds embedded within an EM algorithm.
        
        Documentation
        =============
        
        + Homepage: https://fzhu2e.github.io/GraphEM
        + Installation: https://fzhu2e.github.io/GraphEM/installation.html
        + Tutorial (html): https://fzhu2e.github.io/GraphEM/tutorial.html
        + Tutorial (Jupyter notebooks): https://github.com/fzhu2e/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
        
        
Keywords: GraphEM
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/x-rst
