flat_spots

"Flat spots” are computed by dividing the sample space of a time series into ten equal-sized intervals, and computing the maximum run length within any single interval.

Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.

Rob Hyndman

tsfeatures

Time Series Feature Extraction

Yanfei Kang

Pablo Montero-Manso

Mitchell O'Hara-Wild

Thiyanga Talagala

Earo Wang

Yangzhuoran Yang

Souhaib Ben Taieb

Cao Hanqing

D K Lake

Nikolay Laptev

J R Moorman

Bohan Zhang

flat_spots function

<dl><dt>x</dt>
<dd>a univariate time series</dd></dl>

flat_spots: Longest flat spot

Description

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Author