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v1.0.6 (#9)
* README update * Poetry updates
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README.md

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@@ -29,6 +29,7 @@ Entropy Pooling is a powerful method for implementing subjective views and
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performing stress-tests for fully general Monte Carlo distributions. It was first
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introduced by [Meucci (2008)](https://ssrn.com/abstract=1213325) and refined
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with sequential algorithms by [Vorobets (2021)](https://ssrn.com/abstract=3936392).
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For a quick introduction to Entropy Pooling intuition, watch [this YouTube video](https://youtu.be/qk_5l4ICXfY).
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The original Entropy Pooling approach solves the minimum relative entropy problem
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@@ -38,8 +39,8 @@ subject to the constraints
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$$Gx\leq h \quad \text{and} \quad Ax=b.$$
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The constraints matrices $A$ and $G$ contain transformations of the Monte Carlo
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simulation that allow you to implement subjective views and stress-tests by
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The constraints matrices $A$ and $G$ contain functions of the Monte Carlo
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simulation $R$ that allow you to implement subjective views and stress-tests by
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changing the joint scenario probabilities from a prior probability vector $p$
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to a posterior probability vector $q$.
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