SlidingWindows (version 0.2.0)

entropy.SlidingWindows: Approximate entropy with sliding windows.

Description

This function computes approximate entropy of a univariate time series with sliding windows approach.

Usage

entropy.SlidingWindows(y, w = 99, k = 4, dim = 2, r = 0.5, lag = 1)

Arguments

y

A vector containing univariate time series.

w

An integer value indicating the window size \(w < length(y)\). If \(w = length(y)\), will be computed the function will not slide.

k

An integer value indicating the boundary of the division \((N/k)\). The smallest value of \(k\) is \(4\).

dim

The dimension of given time series. See TSEntropies package.

r

The radius of searched areas. See TSEntropies package.

lag

The downsampling. See TSEntropies package.

Value

A list contaning "w", "ApEn", "FastApEn".

Details

This function return the list with time series sliding windows.

References

Pincus, S.M. (1991). Approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. USA, Vol. 88, pp. 2297<U+2013>2301. doi="doi.org/10.1073/pnas.88.6.2297".

Examples

# NOT RUN {
y <- rnorm(100)
entropy.SlidingWindows(y, w=99, k=4, dim=2, r=.2,lag=1)

# }