[REVIEW]: spatPomp: An R package for spatiotemporal partially observed Markov process models

[editorialbot]

Submitting author: !--author-handle-->@ionides<!--end-author-handle-- (Edward Ionides) Repository: https://github.com/kidusasfaw/spatPomp Branch with paper.md (empty if default branch): joss Version: 0.35.1 Editor: !--editor-->@gkthiruvathukal<!--end-editor-- Reviewers: @bbolker, @johnlees Archive: Pending

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Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@bbolker & @johnlees, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review. First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

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✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @johnlees

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.05 s (2129.2 files/s, 286234.7 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               71           1002           2227           6840
C                               12            272             99           1041
Markdown                         5            188              0            746
make                             3             66              0            189
YAML                             4             27              6            137
TeX                              1             16              0            119
C/C++ Header                     1              8             13             44
-------------------------------------------------------------------------------
SUM:                            97           1579           2345           9116
-------------------------------------------------------------------------------

Commit count by author:

   283  Kidus Asfaw
    94  Ed Ionides
    30  Edward Ionides
    25  Aaron A. King
    11  joonhap
     7  allistho
     2  Jesse Wheeler PC
     1  Aaron A King
     1  Edward L Ionides
     1  Haogao Gu
     1  Jifan Li
     1  Kidus
     1  Ning Ning

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1208

✅ The paper includes a Statement of need section

[editorialbot]

License info:

🟡 License found: GNU General Public License v3.0 (Check here for OSI approval)

[editorialbot]

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

OK DOIs

- 10.1080/01621459.2021.1974867 is OK
- 10.18637/jss.v069.i12 is OK

MISSING DOIs

- No DOI given, and none found for title: A tutorial on spatiotemporal partially observed Ma...
- No DOI given, and none found for title: An introduction to sequential Monte Carlo
- No DOI given, and none found for title: Data assimilation fundamentals: A unified formulat...
- No DOI given, and none found for title: Source code for “Bagged filters for partially obse...
- 10.1109/9780470544334.ch9 may be a valid DOI for title: A new approach to linear filtering and prediction ...
- No DOI given, and none found for title: Inference on spatiotemporal dynamics for networks ...
- No DOI given, and none found for title: Code for “Inference on spatiotemporal dynamics for...
- No DOI given, and none found for title: Iterated block particle filter for high-dimensiona...
- No DOI given, and none found for title: Using an iterated block particle filter via spatPo...
- 10.1007/s11222-020-09957-3 may be a valid DOI for title: Inference on high-dimensional implicit dynamic mod...
- 10.1371/journal.pcbi.1012032 may be a valid DOI for title: Informing policy via dynamic models: Cholera in Ha...
- No DOI given, and none found for title: Source code for “Informing policy via dynamic mode...
- 10.2139/ssrn.4082918 may be a valid DOI for title: Mechanisms for the circulation of influenza A (H3N...

INVALID DOIs

- None

[editorialbot]

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

[johnlees]

Review checklist for @johnlees

Conflict of interest

• [x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• [x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• [x] Repository: Is the source code for this software available at the https://github.com/kidusasfaw/spatPomp?
• [x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• [x] Contribution and authorship: Has the submitting author (@ionides) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• [x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• [x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• [x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• [x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• [x] Installation: Does installation proceed as outlined in the documentation?
• [x] Functionality: Have the functional claims of the software been confirmed?
• [x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• [x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• [x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• [x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• [x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• [x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• [x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• [x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• [x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• [x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
• [x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• [x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[johnlees]

This is a useful piece of software that is a substantial contribution to the field. I have the following comments on the checklist:

Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).

See https://github.com/kidusasfaw/spatPomp/issues/26

Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

See https://github.com/kidusasfaw/spatPomp/issues/27

Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?

The summary is currently very heavy on technical, statistical language. Leading with the example paragraph and giving more details on a use case would perhaps help. 'metapopulations' and 'unit structure' should be defined to non-experts. Changing the order of sentences in the first paragraph would also be sensible, it feels like the order is almost backwards at the moment.

State of the field: Do the authors describe how this software compares to other commonly-used packages?

This is partially done but only with pomp. It would be useful to a general audience why other packages in this domain (e.g. libBi and odin.dust) and more general statistical packages (e.g. stan) don't fulfill the needs that spatPomp does. The sentence 'We are not aware of alternative packages providing statistically efficient, plug-and-play inference for the general class of SpatPOMP models.' would be improved by citing some existing packages and explaining what they do/don't do instead.

[johnlees]

Issues https://github.com/kidusasfaw/spatPomp/issues/26 and https://github.com/kidusasfaw/spatPomp/issues/27 addressed and I have marked those boxes as complete accordingly

[ionides]

@johnlees, thanks again for the feedback on the spatPomp code and manuscript. I'm unsure of the protocols for the open review process at JOSS, but it seems to make sense to respond now to your two points about the manuscript. The revised version is available as paper.pdf on the joss branch of the spatPomp repo (https://github.com/kidusasfaw/spatPomp/blob/joss/paper.pdf).

1. The summary is currently very heavy on technical, statistical language. Leading with the example paragraph and giving more details on a use case would perhaps help. 'metapopulations' and 'unit structure' should be defined to non-experts. Changing the order of sentences in the first paragraph would also be sensible, it feels like the order is almost backwards at the moment.

We have rewritten the summary using this feedback. It now starts with introducing a concrete application and moves toward the general situation, whereas the original submission took the reverse order.

2. It would be useful to a general audience why other packages in this domain (e.g. libBi and odin.dust) and more general statistical packages (e.g. stan) don't fulfill the needs that spatPomp does. The sentence 'We are not aware of alternative packages providing statistically efficient, plug-and-play inference for the general class of SpatPOMP models.' would be improved by citing some existing packages and explaining what they do/don't do instead.

Thank you for pointing out this oversight. Additional discussion of alternative packages is in the extended package tutorial but we agree that this topic should be included also in the relatively brief JOSS overview. We have added some more sentences to the paragraph on the relationship to previous packages, which now reads as follows:

The spatPomp package builds on pomp (King et al. 2016) which is a successful software package for low-dimensional POMP models. Other packages with similar capabilities to pomp include nimble (Michaud et al. 2021), LiBBi (Murray et al. 2015) and mcstate with odin and dust (FitzJohn et al. 2020). All these packages enable plug-and-play inference based on sequential Monte~Carlo. Markov chain Monte Carlo packages, such as stan, have been found to be effective for inference on some POMP models (Li et al. 2018) but they lack the plug-and-play property. Perhaps for that reason, sequential Monte Carlo methods have found broader applicability for this model class. We are not aware of alternative packages to spatPomp that provide statistically efficient, plug-and-play inference for the general class of SpatPOMP models.

[johnlees]

@ionides Thanks for these changes, I think both sections read very well. Thanks also for the small tweaks to the package you already addressed in the issues.

Congratulations and thank you for another useful addition to software packages in this important area. I have marked all the other boxes in my review checklist as complete.