pacf_features: Partial autocorrelation-based features

Description Usage Arguments Value Author(s)

View source: R/thiyanga.R

Description

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

Usage

1

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(s)

Thiyanga Talagala


tsfeatures documentation built on July 1, 2020, 7:12 p.m.