Design of Experiments in Julia
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Updated
Oct 21, 2022 - Julia
Design of Experiments in Julia
Bayesian Information Gap Decision Theory
A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.
This package starts from the monistic thought that bodily facts and conscious facts, though not reducible one to the other, are different sides of one reality. Its originality lies in trying to discover an exact mathematical relation between them.
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