Abstract
Bayesian probability theory offers a powerful framework for the calibration of building energy models (Bayesian calibration). The major issues impeding its routine adoption are its steep learning curve, and the complicated setting up of the required calculation. This paper introduces CALIBRO, an R package which has the objective of facilitating the undertaking of Bayesian calibration of building energy models. An overview of the techniques and procedures involved in CALIBRO is given, as well as demonstrations of its capability and reliability through two examples.
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