[PRE REVIEW]: hetGPy: Heteroskedastic Gaussian Process Modeling in Python

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Submitting author: !--author-handle-->@davidogara<!--end-author-handle-- (David O’Gara) Repository: https://github.com/davidogara/hetGPy Branch with paper.md (empty if default branch): Version: v1.1 Editor: Pending Reviewers: Pending Managing EiC: Chris Vernon

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Software report:

github.com/AlDanial/cloc v 1.90  T=0.11 s (936.2 files/s, 441612.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
SVG                              1              0             39           4938
Python                          48           1126           1769           4167
C++                              3            223             84            994
Jupyter Notebook                14              0          31826            869
CSV                             12              0              0            772
TeX                              1             41              0            462
R                                2             40            205            119
Markdown                         3             49              0             95
reStructuredText                13             34             70             49
YAML                             2              6              8             46
DOS Batch                        1              8              1             26
TOML                             1             10              0             19
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                           102           1541          34009          12565
-------------------------------------------------------------------------------

Commit count by author:

   284  David O'Gara
     9  Mickaël Binois
     1  Lia Schattner

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Paper file info:

📄 Wordcount for paper.md is 1056

✅ The paper includes a Statement of need section

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License info:

🟡 License found: GNU Lesser General Public License v2.1 (Check here for OSI approval)

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Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.1371/journal.pcbi.1009149 is OK
- 10.18637/jss.v098.i13 is OK
- 10.1002/adts.202300147 is OK
- 10.1098/rsos.210506 is OK
- 10.1126/science.abm4247 is OK
- 10.1080/10618600.2018.1458625 is OK
- 10.1080/00401706.2018.1469433 is OK
- 10.48550/arXiv.2002.01321 is OK
- 10.1016/j.epidem.2021.100535 is OK
- 10.1038/s41467-021-27486-z is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.48550/arXiv.1912.01703 is OK
- 10.1145/2049662.2049669 is OK
- 10.1002/9780470770801 is OK
- 10.1007/s00158-013-0919-4 is OK
- 10.7717/peerj-cs.1516 is OK
- 10.21105/joss.04455 is OK
- 10.1111/j.2517-6161.1985.tb01327.x is OK
- 10.1287/opre.1090.0754 is OK
- 10.1038/s41592-019-0686-2 is OK
- 10.1137/0916069 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Bayesian Optimization
- No DOI given, and none found for title: Surrogates: Gaussian Process Modeling, Design and ...
- No DOI given, and none found for title: Modeling and Simulation in Python: An Introduction...
- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python
- No DOI given, and none found for title: BoTorch: A Framework for Efficient Monte-Carlo Bay...
- No DOI given, and none found for title: GPyTorch: Blackbox Matrix-Matrix Gaussian Process ...
- No DOI given, and none found for title: Virtual Library of Simulation Experiments: Test Fu...
- No DOI given, and none found for title: GPflow: A Gaussian Process Library using TensorFlo...
- No DOI given, and none found for title: reticulate: Interface to ’Python’

❌ MISSING DOIs

- 10.1201/9781003226581 may be a valid DOI for title: Modeling and Simulation in Python

❌ INVALID DOIs

- None

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:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

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