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tsfeaturex: An R Package for Automating Time Series Feature Extraction

Authors: Roque, Nelson; Ram, Nilam;

tsfeaturex: An R Package for Automating Time Series Feature Extraction

Abstract

`tsfeaturex` is an R package for automating time series feature extraction, inspired and modeled after the Python package *tsfresh* [@tsfresh; @tsfreshgit]. The R language [@r_cite] allows for an easy to use interface, with the underlying processing speed advantage of C languages (and flexibility to run on the web, with the help of the `shiny` package in R; [@r_shiny]). The API for `tsfeaturex` is a wrapper for the highly-trafficked `dplyr`[@r_dplyr], mainly to lend on the flexibility of the grammar of data manipulation and shortcuts for non-standard evaluation. The API for `tsfeaturex` was designed to facilitate the extraction of features for any dataset in long format, including grouping of summaries by other factor. For example, if every person in your dataset has 1 observation each day for 8 days, and they do this in two bursts, once every 6 months, you can calculate features of the overall series (i.e., 16 observations from both bursts, or separately for each burst). Some features are integrated from other packages, such as: [`e1071`, @r_e1071; `Hmisc`, @r_hmisc; `forecast`, @r_forecast; `zoo`, @r_zoo; `viridis`, @r_viridis; `psych`, @r_psych; `entropy`, @r_entropy; `Langevin`, @Friedrich2011; @Rinn2016]. RELEASE NOTE: Working across multiple R installations across multiple operating systems. For final JOSS submission.

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Keywords

time-series, feature extraction, time series, time-series features

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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