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:

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

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`

:

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

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:

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