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Fixed link in README.rst #32

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4 changes: 2 additions & 2 deletions README.rst
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Expand Up @@ -17,7 +17,7 @@ The algorithm recognizes the input variable type and and uses the appropriate ve
For more information and examples, please visit:

* `wikipedia page on ipf <https://en.wikipedia.org/wiki/Iterative_proportional_fitting>`_
* `slides explaining the methodology and links to specific examples <http://www.demog.berkeley.edu/~eddieh/IPFDescription/AKDOLWDIPFTWOD.pdf>`_
* `slides explaining the methodology and links to specific examples <https://edyhsgr.github.io/IPFDescription/AKDOLWDIPFTHREED.pdf>`_
* https://github.com/Dirguis/ipfn

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Example with the numpy version of the algorithm:
------------------------------------------------
Please, follow the example below to run the package. Several additional examples in addition to the one listed below, are listed in the ipfn.py script. This example is taken from `<http://www.demog.berkeley.edu/~eddieh/IPFDescription/AKDOLWDIPFTHREED.pdf>`_
Please, follow the example below to run the package. Several additional examples in addition to the one listed below, are listed in the ipfn.py script. This example is taken from `<https://edyhsgr.github.io/IPFDescription/AKDOLWDIPFTHREED.pdf>`_

First, let us define a matrix of N=3 dimensions, the matrix being of specific size 2*4*3 and populate that matrix with some values ::

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