The regularity of a time series: the (negative) log-likelihood that patterns
close for m samples stay close for m + 1. Lower = more regular/predictable,
higher = more irregular. The ApEn complement to the package's sample entropy
(ApEn includes self-matches and is more biased for short series, but is the
classical measure).
Usage
approximateEntropy(x, m = 2L, r = NULL)
Arguments
- x
Numeric time series.
- m
Pattern length (default 2).
- r
Tolerance; if NULL, 0.2 * sd(x).
Value
the approximate entropy (scalar).
References
Pincus SM (1991) PNAS 88:2297-2301.
Examples
t <- seq(0, 20 * pi, length.out = 500)
approximateEntropy(sin(t)) # low (regular)
#> [1] 0.2403023
set.seed(1); approximateEntropy(rnorm(500)) # high (irregular)
#> [1] 1.284492