tsrobprep: Robust Preprocessing of Time Series Data

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.

Getting started

Package details

AuthorMichał Narajewski [aut, cre] (<https://orcid.org/0000-0002-3115-0162>), Florian Ziel [aut] (<https://orcid.org/0000-0002-2974-2660>), Jens Kley-Holsteg [ctb]
MaintainerMichał Narajewski <michal.narajewski@uni-due.de>
LicenseMIT + file LICENSE
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("tsrobprep")

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tsrobprep documentation built on April 11, 2021, 5:06 p.m.