Robust Preprocessing of Time Series Data R package tsrobprep version 0.3.2 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) Methods for handling the missing values outliers are introduced in this package. The recognized missing values and outliers are replaced using a model-based approach. The model may consist of both autoregressive components and external regressors. The methods work robust and efficient, and they are fully tunable. The primary motivation for writing the package was preprocessing of the energy systems data, e.g. power plant production time series, but the package could be used with any time series data. For details, see Narajewski et al. (2021) <doi:10.1016/j.softx.2021.100809>. Software Depends: R (>= 3.2.0) Imports: glmnet, MASS, Matrix, mclust, quantreg, Rdpack, splines, textTinyR, zoo Michał Narajewski <michal.narajewski@uni-due.de> Comprehensive R Archive Network (CRAN) Michał Narajewski [aut, cre] (ORCID: <https://orcid.org/0000-0002-3115-0162>), Jens Kley-Holsteg [aut], Florian Ziel [aut] (ORCID: <https://orcid.org/0000-0002-2974-2660>) MIT + file LICENSE (https://CRAN.R-project.org/package=tsrobprep/LICENSE) 2022-02-22 application/tgz https://CRAN.R-project.org/package=tsrobprep doi:10.32614/CRAN.package.tsrobprep