Online

A software package for running highly comparative time-series analysis. hctsa automates the selection of quantitative phenotypes from time-series data by leveraging a large and interdisciplinary literature on time-series analysis. hctsa allows thousands of time-series analysis features to be extracted from time series (or a time-series dataset), as well as tools for normalizing and clustering the data, producing low-dimensional representations of the data, identifying discriminating features between different classes of time series, learning multivariate classification models using large sets of time-series features, finding nearest matches to a time series of interest, and a range of other visualization and analysis functionality.

User report

×
Vote up tools and offer feedback
Give value to tools and make your expertise visible

0 user reviews

0 user reviews

No review has been posted.

hctsa forum

×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.

No open topic.

hctsa versioning

×
Upload and version your source code
Get your DOI for better tool traceability. Archive your releases so the community can easily visualize progress on you work.

No versioning.

hctsa classification

hctsa specifications

Software type:
Framework/Library
Restrictions to use:
None
Programming languages:
MATLAB
Computer skills:
Advanced
Requirements:
Statistics toolbox, Signal Processing Toolbox, Curve Fitting Toolbox, System Identification Toolbox, Wavelet Toolbox, Econometrics Toolbox
Maintained:
Yes
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU General Public License version 3.0
Stability:
Stable
Source code URL:
https://github.com/benfulcher/hctsa.git
Issue URL:
https://github.com/benfulcher/hctsa/issues

hctsa support

Documentation

Maintainer

  • Ben D. Fulcher <>

Credits

×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.

Publications

Institution(s)

Monash Institute of Cognitive and Clinical Neurosciences (MICCN), Monash University, Victoria, Australia; Department of Mathematics, Imperial College London, London, UK

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.