Partial autocorrelation-based features

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

Usage

pacf_features(x)

Arguments

x

a univariate time series

Value

A vector of 3 values: Sum of squared of first 5 partial autocorrelation coefficients of the original series, first differenced series and twice-differenced series. For seasonal data, the partial autocorrelation coefficient at the first seasonal lag is also returned.

Author

Thiyanga Talagala