Update README.md

Author: jbnsn

README.md

@@ -2,18 +2,14 @@
 
 Implementation of [Lindner et al. (2012)](https://www.tandfonline.com/doi/suppl/10.1080/09535314.2012.689954) in Python with NumPy and Pandas.
 
+> Lindner, Sören, Julien Legault, and Dabo Guan. 2012. ‘Disaggregating Input–Output Models with Incomplete Information’. Economic Systems Research 24 (4): 329–47. https://doi.org/10.1080/09535314.2012.689954.
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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).
 
 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.
 
 For verification purposes, e.g. `np.random.seed(1337)` (Python) and `rand('twister', 1337)` (Matlab) can be inserted to render the random numbers predictable.
 
-## Credit: Lindner et al. (2012)
-Lindner, Sören, Julien Legault, and Dabo Guan. 2012.
-‘Disaggregating Input–Output Models with Incomplete Information’.
-Economic Systems Research 24 (4): 329–47.
-https://doi.org/10.1080/09535314.2012.689954.
-
 ## Verification
 The content of `D`.
 ### Matlab