NCCc: Cross-correlation with coefficient normalization

In dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Cross-correlation with coefficient normalization

Description

This function uses the FFT to compute the cross-correlation sequence between two series. They need not be of equal length.

Usage

NCCc(x, y, error.check = TRUE)

Arguments

x, y	Univariate time series.
error.check	Logical indicating whether the function should try to detect inconsistencies and give more informative errors messages. Also used internally to avoid repeating checks.

Value

The cross-correlation sequence with length length(x) + length(y) - 1L.

References

Paparrizos J and Gravano L (2015). “k-Shape: Efficient and Accurate Clustering of Time Series.” In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, series SIGMOD '15, pp. 1855-1870. ISBN 978-1-4503-2758-9, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1145/2723372.2737793")}.

See Also

SBD()

dtwclust documentation built on Sept. 11, 2024, 9:07 p.m.