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tsfeatures

Time Series Feature Extraction

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.

Functions (39)

ac_9

Autocorrelation at lag 9. Included for completion and consistency.

acf_features

Autocorrelation-based features

arch_stat

ARCH LM Statistic

as.list.mts

Convert mts object to list of time series

autocorr_features

The autocorrelation feature set from software package hctsa

binarize_mean

Converts an input vector into a binarized version from software package hctsa

compengine

CompEngine feature set

crossing_points

Number of crossing points

dist_features

The distribution feature set from software package hctsa

embed2_incircle

Points inside a given circular boundary in a 2-d embedding space from software package hctsa

entropy

Spectral entropy of a time series

firstmin_ac

Time of first minimum in the autocorrelation function from software package hctsa

firstzero_ac

The first zero crossing of the autocorrelation function from software package hctsa

flat_spots

Number of flat spots

fluctanal_prop_r1

Implements fluctuation analysis from software package hctsa

heterogeneity

Heterogeneity coefficients

histogram_mode

Mode of a data vector from software package hctsa

holt_parameters

Parameter estimates of Holt's linear trend method

hurst

Hurst coefficient

localsimple_taures

The first zero crossing of the autocorrelation function of the residuals from Simple local time-series forecasting from software package hctsa

lumpiness

Time series features based on tiled windows

max_level_shift

Time series features based on sliding windows

motiftwo_entro3

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

nonlinearity

Nonlinearity coefficient

outlierinclude_mdrmd

How median depend on distributional outliers from software package hctsa

pacf_features

Partial autocorrelation-based features

pred_features

The prediction feature set from software package hctsa

sampen_first

Second Sample Entropy of a time series from software package hctsa

sampenc

Second Sample Entropy from software package hctsa

scal_features

The scaling feature set from software package hctsa

spreadrandomlocal_meantaul

Bootstrap-based stationarity measure from software package hctsa

station_features

The stationarity feature set from software package hctsa

std1st_der

Standard deviation of the first derivative of the time series from software package hctsa

stl_features

Strength of trend and seasonality of a time series

trev_num

Normalized nonlinear autocorrelation, the numerator of the trev function of a time series from software package hctsa

tsfeatures

Time series feature matrix

unitroot_kpss

Unit Root Test Statistics

walker_propcross

Simulates a hypothetical walker moving through the time domain from software package hctsa

yahoo_data

Yahoo server metrics

tsfeatures

Time Series Feature Extraction

v1.0.2

GPL-3

Authors

Rob Hyndman [aut, cre] (<https://orcid.org/0000-0002-2140-5352>), Yanfei Kang [aut] (<https://orcid.org/0000-0001-8769-6650>), Pablo Montero-Manso [aut], Thiyanga Talagala [aut] (<https://orcid.org/0000-0002-0656-9789>), Earo Wang [aut] (<https://orcid.org/0000-0001-6448-5260>), Yangzhuoran Yang [aut], Mitchell O'Hara-Wild [aut] (<https://orcid.org/0000-0001-6729-7695>), Souhaib Ben Taieb [ctb], Cao Hanqing [ctb], D K Lake [ctb], Nikolay Laptev [ctb], J R Moorman [ctb]

Initial release

tsfeatures

Functions (39)

tsfeatures

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