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README.md

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@@ -4,20 +4,19 @@ Implementation of [Lindner et al. (2012)](https://www.tandfonline.com/doi/suppl/
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The comments in `main.py` originate from [`cesr_a_689954_sup_27358897.docx`](https://www.tandfonline.com/doi/suppl/10.1080/09535314.2012.689954).
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The scripts contain one aspect of randomness: `base(p,:) = rand(1,Nv)` in the original Matlab script and `base[p, :] = np.random.rand(1, Nv)` in the Python script.
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The script contains one aspect of randomness: `base(p,:) = rand(1,Nv)` in the original Matlab script and `base[p, :] = np.random.rand(1, Nv)` in the Python script.
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For verification purposes, e.g. `np.random.seed(1337)` (Python) and `rand('twister', 1337)` (Matlab) can be inserted to render the random numbers predictable.
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## Lindner (2012)
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## Credit: Lindner et al. (2012)
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Lindner, Sören, Julien Legault, and Dabo Guan. 2012.
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‘Disaggregating Input–Output Models with Incomplete Information’.
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Economic Systems Research 24 (4): 329–47.
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https://doi.org/10.1080/09535314.2012.689954.
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## Verification (`D`)
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## Verification
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The content of `D`.
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### Matlab
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![main.m](./verification/main.m.png)
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### Python
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![main.m](./verification/main.py.png)

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