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.
|Author||Michał Narajewski [aut, cre] (<https://orcid.org/0000-0002-3115-0162>), Florian Ziel [aut] (<https://orcid.org/0000-0002-2974-2660>), Jens Kley-Holsteg [ctb]|
|Maintainer||Michał Narajewski <firstname.lastname@example.org>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.