acf5: Autocorrelation-based features
In seer: Feature-Based Forecast Model Selection
acf5 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
acf5(y)
Arguments
y
a univariate time series
Value
A vector of 3 values: sum of squared of first five autocorrelation coefficients of original series, first-differenced series,
and twice-differenced series.
Author(s)
Thiyanga Talagala
seer documentation built on Oct. 1, 2022, 9:06 a.m.
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| acf5 | 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
acf5(y)
Arguments
y |
a univariate time series |
Value
A vector of 3 values: sum of squared of first five autocorrelation coefficients of original series, first-differenced series, and twice-differenced series.
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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