localsimple_taures

the forecasting method, default to <code>mean</code>.
<code>mean</code>: local mean prediction using the past trainLength time-series values.
<code>lfit</code>: local linear prediction using the past trainLength time-series values.

forecastMeth

the number of time-series values to use to forecast the next value.
Default to 1 when using method <code>mean</code> and 3 when using method <code>lfit</code>.

trainLength

Simple predictors using the past trainLength values of the time series to
predict its next value.

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

Thiyanga Talagala

Earo Wang

Yangzhuoran Yang

Mitchell O'Hara-Wild

Souhaib Ben Taieb

Cao Hanqing

D K Lake

Nikolay Laptev

J R Moorman

localsimple_taures function

The first zero crossing of the autocorrelation function of the residuals from Simple local time-series forecasting from software package <code>hctsa</code> — localsimple_taures

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

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

Description

Usage

Arguments

Value