TSdist (version 3.6)

WavDistance: Dissimilarity for Time Series Based on Wavelet Feature Extraction

Description

Provides the dissimilarity between two numerical series of the same length by calculating the Euclidean distance between the wavelet coefficients obtained from an orthogonal wavelet transform of the series.

Usage

WavDistance(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.DWT for more information.

Value

d

The computed distance between the pair of series.

Details

This is essentially a wrapper for the diss.DWT function of package TSclust. However, in this case, instead of introducing a matrix conformed of a set of time series, two numerical series of the same length are introduced.

References

Pablo Montero, Jos<U+00E9> 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

# NOT RUN {
# 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 distance based on wavelet feature extraction between the series.

WavDistance(example.series1, example.series2)



# }