Methods for analysis of energy consumption data (electricity, gas, water) at different data measurement intervals. The package provides feature extraction methods and algorithms to prepare data for data mining and machine learning applications. Deatiled descriptions of the methods and their application can be found in Hopf (2019, ISBN:978-3-86309-669-4) "Predictive Analytics for Energy Efficiency and Energy Retailing" <doi:10.20378/irbo-54833> and Hopf et al. (2016) <doi:10.1007/s12525-018-0290-9> "Enhancing energy efficiency in the residential sector with smart meter data analytics".
Version: | 1.0.3 |
Imports: | plyr, futile.logger, FNN, stinepack, zoo |
Suggests: | stringr, knitr, rmarkdown, ROCR, randomForest, caret, dplyr |
Published: | 2020-08-18 |
Author: | Konstantin Hopf |
Maintainer: | Konstantin Hopf <konstantin.hopf at uni-bamberg.de> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Citation: | SmartMeterAnalytics citation info |
CRAN checks: | SmartMeterAnalytics results |
Reference manual: | SmartMeterAnalytics.pdf |
Package source: | SmartMeterAnalytics_1.0.3.tar.gz |
Windows binaries: | r-devel: SmartMeterAnalytics_1.0.3.zip, r-release: SmartMeterAnalytics_1.0.3.zip, r-oldrel: SmartMeterAnalytics_1.0.3.zip |
macOS binaries: | r-release: SmartMeterAnalytics_1.0.3.tgz, r-oldrel: SmartMeterAnalytics_1.0.3.tgz |
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