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ICP #262

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ICP #262

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drcxcruz
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A Julia 1.4.2 translation of the core functionality of R lanague packages
https://cran.r-project.org/web/packages/InvariantCausalPrediction/InvariantCausalPrediction.pdf
https://cran.r-project.org/web/packages/nonlinearICP/nonlinearICP.pdf

Two Jupyter labs showcases the R language version of ICP.

  1. Linear Invariant Causal Prediction Using Employment Data From The Work Bank
    https://notes.quantecon.org/submission/5e851bfecc00b7001acde469

  2. Nonlinear Invariant Causal Prediction Using Unemployment Data and Inflation Adjusted Prices from the USA Bureau of Labor
    https://notes.quantecon.org/submission/5e8e2a6cd079ab001915ca09

New contributions here in Julia are improvements to code readability and support ability.
Also, improvements to program speed such parallelism of random forest computations, p-value linear computations.
There are two version of the InvariantCausalPrediction main functions. One version is sequential and the other parallel.
In addition, there are new VegaLite plots of the InvariantCausalPrediction results.

Cheers,
Clarman Cruz

@sglyon
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sglyon commented Jul 7, 2020

Hi @drcxcruz sorry for the delay in responding to this pull request! This is a significant contribution and we are thankful for your willingness to collaborate.

I'm afraid I don't personally have capacity right now to review this request. Perhaps someone else on the @QuantEcon/lead-developers team does?

If not, I will do my best to find some time in the coming weeks.

Thanks for understanding -- circumstances are far from normal right now!

@drcxcruz
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drcxcruz commented Jul 7, 2020 via email

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