boxcount {RTisean}R Documentation

Renyi entropy estimate

Description

Estimates the Renyi entropy using a partition of the phase space.

Usage

boxcount(series, l, x = 0, c, d = 1, M, Q = 2, R, r, scale = 20)

Arguments

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.

Details

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.

Value

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 Qth order entropy (H_Q(dimension,epsilon)) in the second column and the Qth order differential entropy ( H_Q(dimension,epsilon)-H_Q(dimension-1,epsilon)) in the third column.

References

http://www.mpipks-dresden.mpg.de/~tisean/

See Also

d2, c1

Examples

## 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)

[Package RTisean version 3.0.10 Index]