Open editorialbot opened 3 days ago
Hello human, I'm @editorialbot, a robot that can help you with some common editorial tasks.
For a list of things I can do to help you, just type:
@editorialbot commands
For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:
@editorialbot generate pdf
Software report:
github.com/AlDanial/cloc v 1.90 T=0.19 s (566.3 files/s, 177502.9 lines/s)
-------------------------------------------------------------------------------
Language files blank comment code
-------------------------------------------------------------------------------
Python 76 3868 7034 21263
TeX 1 56 0 533
CSV 3 0 0 439
YAML 8 51 28 192
reStructuredText 17 141 220 174
TOML 1 7 0 58
Markdown 1 17 0 31
DOS Batch 1 8 1 26
make 1 4 7 9
-------------------------------------------------------------------------------
SUM: 109 4152 7290 22725
-------------------------------------------------------------------------------
Commit count by author:
1152 StevenGolovkine
12 Steven
2 dependabot[bot]
1 The Codacy Badger
1 edwardgunning
Paper file info:
📄 Wordcount for paper.md
is 680
✅ The paper includes a Statement of need
section
License info:
✅ License found: MIT License
(Valid open source OSI approved license)
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
✅ OK DOIs
- 10.48550/arXiv.2211.02566 is OK
- 10.5281/zenodo.7117735 is OK
- 10.1007/978-0-387-98185-7 is OK
- 10.18637/jss.v094.i10 is OK
- 10.18637/jss.v093.i05 is OK
- 10.1016/0270-9139(94)90144-9 is OK
- 10.18637/jss.v035.i09 is OK
- 10.48550/arXiv.2310.07330 is OK
- 10.1017/9781108610247 is OK
- 10.48550/arXiv.2211.02566 is OK
- 10.5281/zenodo.7117735 is OK
- 10.1007/978-0-387-98185-7 is OK
- 10.18637/jss.v094.i10 is OK
- 10.18637/jss.v093.i05 is OK
🟡 SKIP DOIs
- No DOI given, and none found for title: PEP8 - Style Guide for Python Code
- No DOI given, and none found for title: Functional Data Analysis
- No DOI given, and none found for title: Inference for Functional Data with Applications
- No DOI given, and none found for title: Introduction to Functional Data Analysis
- No DOI given, and none found for title: Sparse Multivariate Functional Principal Component...
- No DOI given, and none found for title: Multivariate Functional Principal Component Analys...
- No DOI given, and none found for title: On the Use of the Gram Matrix for Multivariate Fun...
- No DOI given, and none found for title: Tslearn, A Machine Learning Toolkit for Time Serie...
- No DOI given, and none found for title: Fda: Functional Data Analysis
- No DOI given, and none found for title: Refund: Regression with Functional Data
- No DOI given, and none found for title: API Design for Machine Learning Software: Experien...
- No DOI given, and none found for title: R: A Language and Environment for Statistical Comp...
- No DOI given, and none found for title: Functional Data Analysis for Sparse Longitudinal D...
- No DOI given, and none found for title: PEP8 - Style Guide for Python Code
- No DOI given, and none found for title: Functional Data Analysis
- No DOI given, and none found for title: Inference for Functional Data with Applications
- No DOI given, and none found for title: Introduction to Functional Data Analysis
- No DOI given, and none found for title: Sparse Multivariate Functional Principal Component...
- No DOI given, and none found for title: Multivariate Functional Principal Component Analys...
- No DOI given, and none found for title: On the Use of the Gram Matrix for Multivariate Fun...
- No DOI given, and none found for title: Tslearn, A Machine Learning Toolkit for Time Serie...
- No DOI given, and none found for title: Fda: Functional Data Analysis
- No DOI given, and none found for title: Refund: Regression with Functional Data
❌ MISSING DOIs
- 10.1080/14763141.2017.1384050 may be a valid DOI for title: Bivariate Functional Principal Components Analysis...
- 10.1016/j.csda.2021.107376 may be a valid DOI for title: Clustering Multivariate Functional Data Using Unsu...
- 10.1016/j.chemolab.2015.09.018 may be a valid DOI for title: Fault Detection of Batch Processes Based on Multiv...
- 10.1109/camsap.2013.6714047 may be a valid DOI for title: Multi-Way Functional Principal Components Analysis
- 10.32614/cran.package.funfem may be a valid DOI for title: funFEM: Clustering in the Discriminative Functiona...
- 10.32614/cran.package.funlbm may be a valid DOI for title: funLBM: Model-Based Co-Clustering of Functional Da...
- 10.32614/cran.package.fdasrvf may be a valid DOI for title: Fdasrvf: Elastic Functional Data Analysis
- 10.32614/cran.package.mfpca may be a valid DOI for title: MFPCA: Multivariate Functional Principal Component...
- 10.1080/14763141.2017.1384050 may be a valid DOI for title: Bivariate Functional Principal Components Analysis...
- 10.1016/j.csda.2021.107376 may be a valid DOI for title: Clustering Multivariate Functional Data Using Unsu...
- 10.1016/j.chemolab.2015.09.018 may be a valid DOI for title: Fault Detection of Batch Processes Based on Multiv...
- 10.1109/camsap.2013.6714047 may be a valid DOI for title: Multi-Way Functional Principal Components Analysis
- 10.32614/cran.package.funfem may be a valid DOI for title: funFEM: Clustering in the Discriminative Functiona...
- 10.32614/cran.package.funlbm may be a valid DOI for title: funLBM: Model-Based Co-Clustering of Functional Da...
- 10.32614/cran.package.fdasrvf may be a valid DOI for title: Fdasrvf: Elastic Functional Data Analysis
- 10.32614/cran.package.mfpca may be a valid DOI for title: MFPCA: Multivariate Functional Principal Component...
❌ INVALID DOIs
- None
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Five most similar historical JOSS papers:
registr 2.0: Incomplete Curve Registration for Exponential Family Functional Data
Submitting author: @bauer-alex
Handling editor: @mbobra (Active)
Reviewers: @qpmnguyen, @g4brielvs
Similarity score: 0.7063
ewstools: A Python package for early warning signals of bifurcations in time series data
Submitting author: @ThomasMBury
Handling editor: @osorensen (Active)
Reviewers: @mhu48, @mikesha2, @ranzhengcode
Similarity score: 0.6934
RENT: A Python Package for Repeated Elastic Net Feature Selection
Submitting author: @annajenul
Handling editor: @mikldk (Retired)
Reviewers: @maximtrp, @arunmano121
Similarity score: 0.6868
tsfeaturex: An R Package for Automating Time Series Feature Extraction
Submitting author: @nelsonroque
Handling editor: @xuanxu (Active)
Reviewers: @acolum, @aj2duncan
Similarity score: 0.6864
Systole: A python package for cardiac signal synchrony and analysis
Submitting author: @LegrandNico
Handling editor: @osorensen (Active)
Reviewers: @axel-loewe, @janfreyberg
Similarity score: 0.6842
⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.
@editorialbot invite @lrnv as editor
:wave: @lrnv - are you available to take this one on?
Invitation to edit this submission sent!
@crvernon Hey thanks for the proposal. I'd rather not since I'm not a python guy and I don't know much about functional data :/
Hi,
Here are some people that may fit to review the paper: James Patrick Horine, mhu48, Lingfeng Luo, Saranraj Nambusubramaniyan, Mahmood Almansoori.
@editorialbot invite @mstimberg as editor
:wave: @mstimberg can you take this one on as editor?
Invitation to edit this submission sent!
Submitting author: !--author-handle-->@StevenGolovkine<!--end-author-handle-- (Steven Golovkine) Repository: https://github.com/StevenGolovkine/FDApy Branch with paper.md (empty if default branch): Version: v1.0.2 Editor: Pending Reviewers: Pending Managing EiC: Chris Vernon
Status
Status badge code:
Author instructions
Thanks for submitting your paper to JOSS @StevenGolovkine. Currently, there isn't a JOSS editor assigned to your paper.
@StevenGolovkine if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.
Editor instructions
The JOSS submission bot @editorialbot is here to help you find and assign reviewers and start the main review. To find out what @editorialbot can do for you type: