PACFDistance {TSdist} | R Documentation |
Partial Autocorrelation-based Dissimilarity
Description
Computes the dissimilarity between a pair of numeric time series based on their estimated partial autocorrelation coefficients.
Usage
PACFDistance(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 |
Details
This is simply a wrapper for the diss.PACF
function of package TSclust. As such, all the functionalities of the diss.PACF
function are also available when using this function.
Value
d |
The computed distance between the pair of series. |
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.
data(example.series3)
data(example.series4)
# For information on their generation and shape see
# help page of example.series.
help(example.series)
# Calculate the autocorrelation based distance between the two series using
# the default parameters:
PACFDistance(example.series3, example.series4)