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5. Assimilating experimental data and models: Bayesian inference
Bayesian inference offers a statistical mathematical framework for assimilating measurement information based on a priori knowledge of elementary or integral parameters, in order to reduce the uncertainties of these parameters and modify their values if necessary.
In the case of nuclear data, the information is microscopic and integral for nuclear data and integral for neutron parameters.
5.1 General principles
Assuming that we are looking for the probability of obtaining the parameters of a model M, where U is the prior knowledge about these parameters and...
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Assimilating experimental data and models: Bayesian inference
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