Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the dissimilarity between two time series in terms of the distance between their integrated periodograms.
1 | diss.INT.PER(x, y, normalize=TRUE)
|
x |
Numeric vector containing the first of the two time series. |
y |
Numeric vector containing the second of the two time series. |
normalize |
If |
The distance is computed as:
d(x,y) = INT( F_x(λ) - F_y(λ))dλ | λ = -π to π
where F_x(λ_j)=(sum F_x(λ_i)|i=1 to j)/C_x and F_y(λ_j)=(sum F_y(λ_i)|i=1 to j)/C_xy, with C_x = ∑_i I_x(λ_i) and C_y = ∑_i I_y(λ_i) in the normalized version. C_x = 1 and C_y = 1 in the non-normalized version. I_x(λ_k) and I_y(λ_k) denote the periodograms of x
and y
, respectively.
The computed distance.
Pablo Montero Manso, José Antonio Vilar.
Casado de Lucas, D. (2010) Classification techniques for time series and functional data.
Montero, P and Vilar, J.A. (2014) TSclust: An R Package for Time Series Clustering. Journal of Statistical Software, 62(1), 1-43. http://www.jstatsoft.org/v62/i01/.
1 2 3 4 5 6 7 8 9 10 11 12 | ## Create three sample time series
x <- cumsum(rnorm(100))
y <- cumsum(rnorm(100))
z <- sin(seq(0, pi, length.out=100))
## Compute the distance and check for coherent results
diss.INT.PER(x, y, normalize=TRUE)
diss.INT.PER(x, y, normalize=TRUE)
diss.INT.PER(x, y, normalize=TRUE)
## Not run:
diss( rbind(x,y,z), "INT.PER", normalize=FALSE )
## End(Not run)
|
Loading required package: wmtsa
Loading required package: pdc
Loading required package: cluster
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE
3: .onUnload failed in unloadNamespace() for 'rgl', details:
call: fun(...)
error: object 'rgl_quit' not found
[1] 2.629073
[1] 2.629073
[1] 2.629073
x y
y 22465.330
z 9214.179 31679.508
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