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Özer, S and Jacoby, S (2022) Dwelling size and usability in London: a study of floor plan data using machine learning. Building Research & Information, 50(06), 694–708.

Acharya, P, Sharma, K, Pokharel, G R and Adhikari, R (2022) Reviewing the progress of reconstruction five years after the 2015 Gorkha earthquake, Nepal. Building Research & Information, 50(06), 595–609.

Ade, R and Rehm, M (2022) A summertime thermal analysis of New Zealand Homestar certified apartments for older people. Building Research & Information, 50(06), 681–93.

Mushi, F V, Nguluma, H and Kihila, J (2022) A critical review of African green building research. Building Research & Information, 50(06), 610–27.

Mustaffa, N K, Abdul Kudus, S, Abdul Aziz, M F H and Anak Joseph, V R (2022) Strategies and way forward of low carbon construction in Malaysia. Building Research & Information, 50(06), 628–45.

Outcault, S, Alston-Stepnitz, E, Sanguinetti, A, DePew, A N and Magaña, C (2022) Building lower-carbon affordable housing: case studies from California. Building Research & Information, 50(06), 646–61.

Zhuravchak, R, Nord, N and Brattebø, H (2022) The effect of building attributes on the energy performance at a scale: an inferential analysis. Building Research & Information, 50(06), 662–80.

  • Type: Journal Article
  • Keywords: Built stock; energy performance; probabilistic programming; combinatorial analysis; frequentist inference; univariate density estimation; statistical hypothesis testing;
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2022.2038537
  • Abstract:
    The commitments to mitigate the negative impacts associated with final energy use stipulate the increase of energy efficiency of the built environment. This is the focus of urban energy policies and of built stock energy models that aid them. The complexities behind the phenomenon, however, hinder the development of the means for controlling and unbiased modelling. Such tasks necessitate the empirical evidence of causal relationships between architectural and technical attributes and building energy performance at the population level. This study, therefore, elaborates on the methods of inferential statistics for establishing such causal effects. The focus is on the methods of frequentist inference, active use of which may advance the understanding of the phenomenon and foster more accurate modelling practices. The case study examines the energy performance exhibited by distinct configurations of construction periods, envelope materials, sources of energy for space heating and the ventilation system types. The empirical sample consists of more than 11,000 records registered in the Norwegian energy performance certification system. The results document the effects and their significance. These methods are applicable in any urban context and may provide the empirical basis for promoting/discouraging certain technological and architectural tendencies, and simulating the phenomena through probabilistic programming.