acf_features: Autocorrelation-based features
In tsfeatures: Time Series Feature Extraction
acf_features R Documentation
Autocorrelation-based features
Description
Computes various measures based on autocorrelation coefficients of the
original series, first-differenced series and second-differenced series
Usage
acf_features(x)
Arguments
x
a univariate time series
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
tsfeatures documentation built on Aug. 28, 2023, 5:09 p.m.
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| acf_features | R Documentation |
Autocorrelation-based features
Description
Computes various measures based on autocorrelation coefficients of the original series, first-differenced series and second-differenced series
Usage
acf_features(x)
Arguments
x |
a univariate time series |
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
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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