Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23272
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A comparison of approaches to stepwise regression on variables sensitivities in building simulation and analysis
Authors: Wang, Mengchao
Wright, Jonathan
Brownlee, Alexander
Buswell, Richard
Contact Email: sbr@cs.stir.ac.uk
Keywords: Global sensitivity analysis
Stepwise regression
Sensitivity indexes
Standardized (rank) regression coefficients
Issue Date: Sep-2016
Publisher: Elsevier
Citation: Wang M, Wright J, Brownlee A & Buswell R (2016) A comparison of approaches to stepwise regression on variables sensitivities in building simulation and analysis, Energy and Buildings, 127, pp. 313-326.
Abstract: Developing sensitivity analysis (SA) that reliably and consistently identify sensitive variables can improve building performance design. In global SA, a linear regression model is normally applied to sampled-based solutions by stepwise manners, and the relative importance of variables is examined by sensitivity indexes. However, the robustness of stepwise regression is related to the choice of procedure options, and therefore influence the indication of variables’ sensitivities. This paper investigates the extent to which the procedure options of a stepwise regression for design objectives or constraints can affect variables global sensitivities, determined by three sensitivity indexes. Given that SA and optimization are often conducted in parallel, desiring for a combined method, the paper also investigates SA using both randomly generated samples and the biased solutions obtained from an optimization run. Main contribution is that, for each design objective or constraint, it is better to conclude the categories of variables importance, rather than ordering their sensitivities by a particular index. Importantly, the overall stepwise approach (with the use of bidirectional elimination,BIC, rank transformation and 100 sample size) is robust for global SA: the most important variables are always ranked on the top irrespective of the procedure options.
Type: Journal Article
URI: http://hdl.handle.net/1893/23272
DOI Link: http://dx.doi.org/10.1016/j.enbuild.2016.05.065
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Wang M, Wright J, Brownlee A & Buswell R (2016) A comparison of approaches to stepwise regression on variables sensitivities in building simulation and analysis, Energy and Buildings, 127, pp. 313-326 DOI: 10.1016/j.enbuild.2016.05.065 © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Affiliation: Loughborough University
Loughborough University
Computing Science - CSM Dept
Loughborough University

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