feat_acf: Autocorrelation-based features

In tidyverts/tsibblestats: Feature Extraction and Statistics for Time Series

Autocorrelation-based features

Description

Computes various measures based on autocorrelation coefficients of the original series, first-differenced series and second-differenced series

Usage

feat_acf(x, .period = 1, lag_max = NULL, ...)

Arguments

x	a univariate time series
.period	The seasonal period (optional)
lag_max	maximum lag at which to calculate the acf. The default is max(.period, 10L) for feat_acf, and max(.period, 5L) for feat_pacf
...	Further arguments passed to stats::acf() or stats::pacf()

Value

A vector of 6 values: first autocorrelation coefficient and sum of squared of first ten autocorrelation coefficients of original series, first-differenced series, and twice-differenced series. For seasonal data, the autocorrelation coefficient at the first seasonal lag is also returned.

Author(s)

Thiyanga Talagala

tidyverts/tsibblestats documentation built on March 18, 2024, 9:47 a.m.