shapeBasedDistance: Shape-Based Distance
In Jakob-Bach/FastTSDistances: Fast dissimilarity computations for time series
Description
Usage
Arguments
Value
References
See Also
Description
Computes the dissimilarity as 1 - maximum normalized cross-correlation
coefficient as described by Paparrizos and Gravano (2015). Multi-variate
time series are handled by calculating the cross-correlation between corresponding
attributes in x and y, averaging over attributes and then taking
the average cross-correlation at the lag which maximizes it.
Usage
1
shapeBasedDistance(x, y)
Arguments
x
1st numeric vector/time series.
y
2nd numeric vector/time series.
Value
The dissimilarity as numeric from the range [0,2].
References
Paparrizos, J. & 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 (pp. 1855–1870). ACM.
See Also
Other cross-correlation functions: crossCorNormalized
Jakob-Bach/FastTSDistances documentation built on May 13, 2019, 1:15 p.m.
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.
Description Usage Arguments Value References See Also
Description
Computes the dissimilarity as 1 - maximum normalized cross-correlation
coefficient as described by Paparrizos and Gravano (2015). Multi-variate
time series are handled by calculating the cross-correlation between corresponding
attributes in x and y, averaging over attributes and then taking
the average cross-correlation at the lag which maximizes it.
Usage
1 | shapeBasedDistance(x, y)
|
Arguments
x |
1st numeric vector/time series. |
y |
2nd numeric vector/time series. |
Value
The dissimilarity as numeric from the range [0,2].
References
Paparrizos, J. & 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 (pp. 1855–1870). ACM.
See Also
Other cross-correlation functions: crossCorNormalized
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.