Calibration of every computational code. It uses a Bayesian framework to rule the estimation. With a new data set, the prediction will create a prevision set taking into account the new calibrated parameters. The choices between several models is also available. The methods are described in the paper Carmassi et al. (2018) <arXiv:1801.01810>.
|Author||Mathieu Carmassi [aut, cre]|
|Maintainer||Mathieu Carmassi <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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