@incollection{booth2012calibrating,
  title = {Calibrating Micro-Level Models with Macro-Level Data Using Bayesian Regression Analysis},
  booktitle = {Proceedings of the 12th {{IBPSA}} Conference, November 14--16},
  author = {Booth, Adam and Choudhary, Ruchi and Initiative, Energy Efficient Cities},
  year = {2012},
  pages = {641--648},
  abstract = {Bottom-up engineering-based housing stock models play a useful role in assessing the impact of retrofits for residential buildings. Such models require calibrating, using micro-level energy measurements, to improve model accuracy; however, the only publicly available data for the UK housing stock is at the macro-level. This paper outlines a method for using macro-level data to calibrate micro-level models. A combination of regression analysis and Bayesian inference is pro- posed. The result is a Bayesian regression method that generates estimates of the average energy use for different dwelling types, whilst quantifying uncertainty in the empirical energy data and the generated energy estimates.}
}

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