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This submission is currently in a pre-review state which means we are waiting for an editor to be assigned and for them to find some reviewers for your submission. This may take anything between a few hours to a couple of weeks. Thanks for your patience 😸

You can help the editor by looking at this list of potential reviewers to identify individuals who might be able to review your submission (please start at the bottom of the list). Also, feel free to suggest individuals who are not on this list by mentioning their GitHub handles here.

Attempting PDF compilation. Reticulating splines etc...

👉 Check article proof 📄 👈

👋 @katyhuff - the submitter requested you as the editor - are you willing to accept?

yes!

@whedon assign @katyhuff as editor

OK, the editor is @katyhuff

Thank you for your submission @prmiles . I'll now identify appropriate reviewers and request their assistance with this review.

I've found some great folks. Now @prmiles , let's ping a few fitting reviewers, with python, statistics (ideally bayesian), and some computational physics expertise. We can start the review once two or three of them accept the request to review.

Dear @jarvist :

I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

Dear @ivergara :

I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

Dear @djmitche:

I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

Dear @malmaud:

I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

Dear @betatim:
I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

Dear @ejolly:

I have identified you as a fitting reviewer for this paper, which will require experts with python, statistics (ideally bayesian), and some computational physics expertise. Are you able to and interested in taking on this JOSS review?

Title: pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Summary: A Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques including Metropolis-Hastings, Adaptive-Metropolis, Delayed-Rejection, and Delayed Rejection Adaptive Metropolis. This Python package is an adaptation of the MATLAB toolbox mcmcstat.
Article Proof: https://github.com/openjournals/joss-papers/blob/joss.01401/joss.01401/10.21105.joss.01401.pdf
Submitting author: @prmiles (Paul Miles)
Repository: https://github.com/prmiles/pymcmcstat
Version: v1.7.0

I have good experience in Python and minimal statistical experience. On that basis, I'm happy to help.

@djmitche : Thank you! I particularly hoped that you could contribute with regard to reviewing the testing coverage!

@whedon assign @djmitche as reviewer

OK, the reviewer is @djmitche

This software package has good overlap with my expertise, and I am happy to review. As the package is quite extensive in features and size of code-base, review may take a while.

@jarvist : Thank you! I appreciate your engagement. If good software-development practices have been employed, I've found that even large code bases become much more straightforward to review. It is my hope this is the case with this submission. We'll start the review as soon as we have one more reviewer.

@whedon add @jarvist as reviewer

OK, @jarvist is now a reviewer

@katyhuff unfortunately I cannot take this review, Bayesian statistics falls (at the moment) too far from my knowledge corpus to be able to provide a good feedback on how the package works.

Thank you for letting me know @ivergara .