ESGtoolkit, a tool for Monte Carlo simulation (v0.2.0)

January 16, 2020
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[This article was first published on T. Moudiki's Webpage - R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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I’m still receiving questions about ESGtoolkit – a tool that I developped in 2014 for stochastic simulation – from time to time, even if it’s not really my current focus. As I also noticed recently, ESGtoolkit is downloaded a few times each month:

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If you recognize yourself in these numbers, I’d be really happy to hear from you (via thierry dot moudiki at pm dot me or a pull request on Github), about your use of ESGtoolkit. This will prevent me from accidentally breaking the interface, and you won’t ask yourself “it worked perfectly yesterday, why is it broken today?”.

I decided to declutter it a little bit on Github, so that it can host your future contributions/remarks/suggestions. The new version, v0.2.0, contains an updated vignette and a refactored code. Simulation functions simdiff and simshocks include a reproducibility seed (random state) now, for you to be able to… reproduce your simulations from one function call to the other.

Package vignette should be a good introduction. Otherwise, if this vignette is too technical, please refer to these blog posts, here and here, or this presentation.

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Contributions/remarks/suggestions are welcome as usual. You can submit a pull request on Github or send me an email: thierry dot moudiki at pm dot me.

Note: I am currently looking for a gig. You can hire me on Malt or send me an email: thierry dot moudiki at pm dot me. I can do descriptive statistics, data preparation, feature engineering, model calibration, training and validation, and model outputs’ interpretation. I am fluent in Python, R, SQL, Microsoft Excel, Visual Basic (among others) and French. My résumé? Here!

To leave a comment for the author, please follow the link and comment on their blog: T. Moudiki's Webpage - R.

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