boxcount {RTisean} | R Documentation |
Estimates the Renyi entropy using a partition of the phase space.
boxcount(series, l, x = 0, c, d = 1, M, Q = 2, R, r, scale = 20)
series |
a vector or a matrix. |
l |
number of data to use. |
x |
number of lines to be ignored. |
c |
column to be read. |
d |
delay for the delay vectors. |
M |
number of components, maximal embedding dimension. |
Q |
order of the entropy. |
R |
maximal length scale. |
r |
minimal length scale. |
scale |
number of epsilon values. |
This function also can handle multivariate data, so that the phase space is built of the components of the time series plus a temporal embedding, if desired.
A list containing as many lists as the number of components,
each containing as many matrices as the number of dimensions.
Each matrix contains: the value of epsilon
in the first column, the Q
th order entropy (H_Q(dimension,epsilon))
in the second column and the Q
th order differential entropy
( H_Q(dimension,epsilon)-H_Q(dimension-1,epsilon)) in the third column.
http://www.mpipks-dresden.mpg.de/~tisean/
## Not run: dat <- henon(10000) boxout<- boxcount(dat,d=2) plot(boxout[[1]][,1],boxout[[1]][,2],ylim=c(0,8), t="l", xlab="Epsilon",ylab="Entropy",main="Renyi Entropy of Henon Data") lines(boxout[[2]][,1],boxout[[2]][,2],t="l",col=2) legend(1.5,7, c("Embedding dimension 1", "Embedding dimension 2"),fill=c(1,2), bty="n") ## End(Not run)