TSdist (version 3.2)

SpecLLRDistance: General Spectral Dissimilarity Measure Using Local-Linear Estima- tion of the Log-Spectra

Description

The dissimilarity of two numerical series of the same length is calculated based on the ratio between local linear estimations of the log-spectras.

Usage

SpecLLRDistance(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.SPEC.LLR for more information.

Value

• d
  The computed distance between the pair of series.

Details

This is simply a wrapper for the diss.SPEC.LLR function of package TSclust. As such, all the functionalities of the diss.SPEC.LLR function are also available when using this function. Note: This distance measure is not a metric (Montero and Vilar, 2014), but the negative definiteness is not explicitly confirmed or discarded in the literature, to the extent of our knowledge. As such, before using it directly within kernel machines (for example, by inserting it in the Gaussian RBF kernel), we recommend analyzing the positive definiteness of the Gram matrix, which is a requirement for kernel based classifiers such as Support Vector Machines or Gaussian Processes. More information and some solutions to this problem can be found in (Pree, 2014).

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 spec.isd distance between the two series using
# the default parameters. 

SpecLLRDistance(example.series1, example.series2)