| d2 {RTisean} | R Documentation |
Estimates the correlation sum, the correlation dimension and the correlation entropy of a given, possibly multivariate, time series.
d2(series, l, x = 0, d = 1, M, c, t = 0, R, r, scale = 100, N = 1000, E = FALSE, pretty=FALSE)
series |
a vector or matrix. |
l |
number of data points to be used. |
x |
number of lines to be ignored. |
d |
delay for the delay vectors. |
M |
number of components, maximal embedding dimension |
c |
columns to be read. |
t |
theiler window. |
R |
maximal length scale. |
r |
minimal length scale. |
scale |
number of epsilon values. |
N |
maximal number of pairs to be used. |
E |
use data that is normalized to [0,1] for all components. |
pretty |
clean ouput for pretty printing |
The parameter pretty must be set to FALSE if the output of d2 is
meant to be post-processed by av_d2, c2d,cdg or c2t.
A list of lists, each composed by as many matrices as the treated length scales and embedding dimensions. The first column of each matrix contains the values of epsilon; the second column contains, according to the list item:
.c2 |
the correlation sums. |
.d2 |
the local slopes of the logarithm of the correlation sum, the correlation dimension. |
.h2 |
the correlation entropies. |
## Not run:
dat <- henon(10000)
d2output <- d2(dat, pretty=TRUE)
cordim <- d2output$.d2
plot(cordim[[1]],t="l",ylim=c(0,7),col=2,xlab="Epsilon",
ylab=expression(D[2](m,epsilon)),log="x", main="Correlation Dimension Plot")
for (a in 2:10)
lines(cordim[[a]],col=2)
## End(Not run)