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Data and code for Jia and Chong (2020): Hongyuan Jia and Adrian Chong (2020). eplusr: A framework for integrating building energy simulation and data-driven analytics. (Accepted in Energy and Buildings).

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ideas-lab-nus/eplusr-paper

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eplusr framework

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This repository contains the data and code for paper:

Hongyuan Jia and Adrian Chong, (2020). A framework for integrating building energy simulation and data-driven analytics. (In review)

How to cite

Please cite this compendium as:

Hongyuan Jia and Adrian Chong, (2020). Compendium of R code and data for A framework for integrating building energy simulation and data-driven analytics. Accessed 05 Jul 2020.

How to download or install

(a) Option 1: Download the compiled draft PDF

The latest compiled draft PDF can be downloaded from the ActionsArtifacts.

(b) Option 2: Download the compendium and compile the PDF

You can download the compendium as a zip from from this URL: https://github.com/ideas-lab-nus/eplusr-paper/archive/master.zip

Or you can install this compendium as an R package, eplusr-paper, from GitHub with:

# install.packages("remotes")
remotes::install_github("ideas-lab-nus/eplusr-paper")

The PDF can be compiled via:

rmarkdown::render('vignettes/paper.Rmd')

Licenses

Text and figures : CC-BY-4.0

Code : See the DESCRIPTION file

Data : CC-0 attribution requested in reuse

Contributions

We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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Data and code for Jia and Chong (2020): Hongyuan Jia and Adrian Chong (2020). eplusr: A framework for integrating building energy simulation and data-driven analytics. (Accepted in Energy and Buildings).

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Unknown, MIT licenses found

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LICENSE
MIT
LICENSE.md

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