arch_stat

Computes a statistic based on the Lagrange Multiplier (LM) test of Engle (1982) for
autoregressive conditional heteroscedasticity (ARCH). The statistic returned is
the \(R^2\) value of an autoregressive model of order <code>lags</code> applied
to \(x^2\).

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

arch_stat function

<dl><dt>x</dt>
<dd>a univariate time series</dd>
<dt>lags</dt>
<dd>Number of lags to use in the test</dd>
<dt>demean</dt>
<dd>Should data have mean removed before test applied?</dd></dl>

Arguments

Author

ARCH LM Statistic — arch_stat

<dl>

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


<dt>lags</dt>
<dd>Number of lags to use in the test</dd>


<dt>demean</dt>
<dd>Should data have mean removed before test applied?</dd>

</dl>

ARCH LM Statistic

arch_stat: ARCH LM Statistic

Description

Usage

Value

Arguments

Author