R package for the calculation of 22 CAnonical Time-series CHaracteristics. The package is an efficient implementation that calculates time-series features coded in C.

You can install the stable version of `Rcatch22`

from CRAN
using the following:

`install.packages("Rcatch22")`

You can install the development version of `Rcatch22`

from
GitHub using the following:

`::install_github("hendersontrent/Rcatch22") devtools`

You might also be interested in a related R package called `theft`

(Tools for Handling Extraction of Features from Time series) which
provides standardised access to `Rcatch22`

and 5 other
feature sets (including 3 feature sets from Python libraries) for a
total of ~1,200 features. `theft`

also includes extensive
functionality for processing and analysing time-series features,
including automatic time-series classification, top performing feature
identification, and a range of statistical data visualisations.

Please open the included vignette within an R environment or visit
the detailed `Rcatch22`

Wiki for information and tutorials.

With features coded in C, `Rcatch22`

is highly
computationally efficient, scaling nearly linearly with time-series
size. Computation time in seconds for a range of time series lengths is
presented below.

An option to include the mean and standard deviation as features in
addition to `catch22`

is available through setting the
`catch24`

argument to `TRUE`

:

`<- catch22_all(x, catch24 = TRUE) features `

A DOI is provided at the top of this README. Alternatively, the package can be cited using the following:

```
To cite package 'Rcatch22' in publications use:
Trent Henderson (2022). Rcatch22: Calculation of 22 CAnonical
Time-Series CHaracteristics. R package version 0.2.1.
A BibTeX entry for LaTeX users is
@Manual{,
title = {Rcatch22: Calculation of 22 CAnonical Time-Series CHaracteristics},
author = {Trent Henderson},
year = {2022},
note = {R package version 0.2.1},
}
```

Please also cite the original *catch22* paper: