TSdist (version 3.2)

ARMahDistance: Model-based Dissimilarity Proposed by Maharaj (1996, 2000)

Description

Computes the model based dissimilarity proposed by Maharaj.

Usage

ARMahDistance(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.AR.MAH for more information.

Value

• statistic
  The statistic of the homogeneity test.
• p-value
  The p-value issued by the homogeneity test.

Details

This is simply a wrapper for the diss.AR.MAH function of package TSclust. As such, all the functionalities of the diss.AR.MAH function are also available when using this function. Note: The negative definiteness of this distance measure is not explicitly mentioned in the literature, to the best of our knowledge, and so cannot be assured. As such, when using it within kernel based classifiers such as Support Vector Machines or Gaussian Processes (i.e by inserting this distance in the Gaussian RBF kernel) the user should make sure that the obtained Gram matrix is positive semi-definite. More information and references to some solutions to this problem can be found in (Pree et al. 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.series3 and example.series4 are two 
# numeric series of length 100 and 120 contained in the 
# TSdist package obtained from an ARIMA(3,0,2) process. 

data(example.series3)
data(example.series4)

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

help(example.series)

# Calculate the ar.mah distance between the two series using
# the default parameters. 

ARMahDistance(example.series3, example.series4)

# The p-value is almost 1, which indicates that the two series come from the same 
# ARMA process.