CIDDistance: Complexity-Invariant Distance Measure For Time Series

In TSdist: Distance Measures for Time Series Data

Complexity-Invariant Distance Measure For Time Series

Description

Computes the dissimilarity between two numeric series of the same length by calculating a correction of the Euclidean distance based on the complexity estimation of the series.

Usage

CIDDistance(x, y)

Arguments

x	Numeric vector containing the first time series.
y	Numeric vector containing the second time series.

Details

This is simply a wrapper for the diss.CID function of package TSclust. As such, all the functionalities of the diss.CID 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/.

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 compression based distance between the two series using
# the default parameters. 

CIDDistance(example.series1, example.series2)

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