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

In TSdist: Distance Measures for Time Series Data

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.

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.

Value

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

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.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. 

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