Identifying key variables and interactions in statistical models of building energy consumption using regularization

Statistical models can only be as good as the data put into them. Data about energy consumption continues to grow, particularly its non-technical aspects, but these variables are often interpreted differently among disciplines, datasets, and contexts. Selecting key variables and interactions is therefore an important step in achieving more accurate predictions, better interpretation, and identification of key subgroups for further analysis.

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Year of publication:	2015
Authors:	Hsu, David
Published in:	Energy. - Elsevier, ISSN 0360-5442. - Vol. 83.2015, C, p. 144-155
Publisher:	Elsevier
Subject:	Energy consumption \| Buildings \| Variable selection \| Statistical models

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011264361