TSdist (version 2.2)

ar.picDistance: Model-based Dissimilarity Measure Proposed by Piccolo (1990)

Description

Computes the model based dissimilarity proposed by Piccolo.

Usage

ar.picDistance(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.PIC for more information.

Value

• d
  The computed distance between the pair of series.

Details

This is simply a wrapper for the diss.AR.PIC function of package TSclust. As such, all the functionalities of the diss.AR.PIC function are also available when using this function.

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 Piccolo distance between the two series using
#the default parameters. In this case an AR model is automatically 
#selected for each of the series:

ar.picDistance(example.series3, example.series4)

#Calculate the Piccolo distance between the two series
#imposing the order of the ARMA model of each series:

ar.picDistance(example.series3, example.series4, order.x=c(3,0,2), 
order.y=c(3,0,2))