motiftwo_entro3: Local motifs in a binary symbolization of the time series...

In tsfeatures: Time Series Feature Extraction

Local motifs in a binary symbolization of the time series from software package hctsa

Description

Coarse-graining is performed. Time-series values above its mean are given 1, and those below the mean are 0.

Usage

motiftwo_entro3(y)

Arguments

y	the input time series

Value

Entropy of words in the binary alphabet of length 3.

Author(s)

Yangzhuoran Yang

References

B.D. Fulcher and N.S. Jones. hctsa: A computational framework for automated time-series phenotyping using massive feature extraction. Cell Systems 5, 527 (2017).

B.D. Fulcher, M.A. Little, N.S. Jones Highly comparative time-series analysis: the empirical structure of time series and their methods. J. Roy. Soc. Interface 10, 83 (2013).

Examples

motiftwo_entro3(WWWusage)

tsfeatures documentation built on Aug. 28, 2023, 5:09 p.m.