Rcatch22

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.

Installation

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 standardized access to Rcatch22 and several other feature sets in both R and Python for a total of >6,600 features (including enabling you to calculate your own custom features).

Wiki

Please open the included vignette within an R environment or visit the detailed catch22 gitbook for detailed information on all the features and implementations in various programming languages.

Computational performance

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.

catch24

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)

Citation

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:

  Henderson T (2026). _Rcatch22: Calculation of 22 CAnonical
  Time-Series CHaracteristics_. R package version 0.2.5.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {Rcatch22: Calculation of 22 CAnonical Time-Series CHaracteristics},
    author = {Trent Henderson},
    year = {2026},
    note = {R package version 0.2.5},
  }

Please also cite the original catch22 paper:

• Lubba et al. (2019). catch22: CAnonical Time-series CHaracteristics.