TSdist (version 2.1)

ccorDistance: Cross-correlation based distance.

Description

Computes the distance measure based on the cross-correlation between a pair of numeric time series.

Usage

ccorDistance(x, y, lag.max=(min(length(x), length(y))-1))

Arguments

x

Numeric vector containing the first time series.

y

Numeric vector containing the second time series.

lag.max

Positive integer that defines the maximum lag considered in the cross-correlation calculations (default=min(length(x), length(y))-1).

Value

• d
  The computed distance between the pair of series.

Details

The cross-correlation based distance between two numeric time series is calculated as follows:

$$D= \sqrt{ ((1 - CC(x, y, 0) ^ 2) / \sum (1 - CC(x, y, k) ^ 2)) }$$

where $CC(x,y,k)$ is the cross-correlation between $x$ and $y$ at lag $k$. The summatory in the denominator goes from 1 to lag.max. In view of this, the parameter must be a positive integer no larger than the length of the series.

References

Liao, T. W. (2005). Clustering of time series data-a survey. Pattern Recognition, 38(11), 1857-1874.

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 cross-correlation based distance 
#using the default lag.max.

ccorDistance(example.series3, example.series4)

#Calculate the cross-correlaion based distance 
#with lag.max=50.

ccorDistance(example.series3, example.series4, lag.max=50)