CortDistance: Dissimilarity Index Combining Temporal Correlation and Raw...

In TSdist: Distance Measures for Time Series Data

Dissimilarity Index Combining Temporal Correlation and Raw Value Behaviors

Description

Computes the dissimilarity between two numeric series of the same length by combining the dissimilarity between the raw values and the dissimilarity between the temporal correlation behavior of the series.

Usage

CortDistance(x, y, ...)

Arguments

x	Numeric vector containing the first time series.
y	Numeric vector containing the second time series.
...	Additional parameters for the function. See diss.CORT for more information.

Details

This is simply a wrapper for the diss.CORT function of package TSclust. As such, all the functionalities of the diss.CORT function are also available when using this function.

Value

d	The computed distance between the pair of series.

Author(s)

Usue Mori, Alexander Mendiburu, Jose A. Lozano.

References

Pablo Montero, José A. Vilar (2014). TSclust: An R Package for Time Series Clustering. Journal of Statistical Software, 62(1), 1-43. URL http://www.jstatsoft.org/v62/i01/.

Chouakria, A. D., & Nagabhushan, P. N. (2007). Adaptive dissimilarity index for measuring time series proximity. Advances in Data Analysis and Classification, 1(1), 5–21. http://doi.org/10.1007/s11634-006-0004-6

See Also

To calculate this distance measure using ts, zoo or xts objects see TSDistances. To calculate distance matrices of time series databases using this measure see TSDatabaseDistances.

Examples

# The objects example.series1 and example.series2 are two 
# numeric series of length 100.

data(example.series1)
data(example.series2)

# For information on their generation and shape see 
# help page of example.series.

help(example.series)

# Calculate the first correlation based distance between the series using the default 
# parameters.

CortDistance(example.series1, example.series2)

TSdist documentation built on Aug. 31, 2022, 5:09 p.m.