Abstract
We add a random variable type to a mathematical modeling language. We demonstrate through examples how this is a highly separable way to introduce uncertainty and produce and query stochastic models. We motivate the use of symbolics and thin compilers in scientific computing.
Cite
CITATION STYLE
APA
Rocklin, M. (2012). Uncertainty Modeling with SymPy Stats. In Proceedings of the 11th Python in Science Conference (pp. 51–55). SciPy. https://doi.org/10.25080/majora-54c7f2c8-009
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