Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
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Updated
Jun 3, 2024 - Julia
Error (or uncertainty) propagation is the practice of analyzing and accounting for the effect of numeric quantities' uncertainties on the results of functions that involve them.
When variables used in a function or mathematical operation have errors (due to measurement uncertainties, random fluctuations, sample variance, etc.), error propagation can be used to determine the resulting error of the function's output.
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
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