<unk>  (RPDE) is a method, in the fields of dynamical systems, stochastic processes, and time series analysis, for determining the<unk> icity, or repetitiveness of a signal.<unk>  is useful for characterizing the extent to which a time series repeats the same sequence, and is therefore similar to linear autocorrelation and time delayed mutual information, except that it measures repetitiveness in the phase space of the system, and is thus a more reliable measure based upon the dynamics of the underlying system that generated the signal. It has the advantage that it does not require the assumptions of linearity, Gaussianity or dynamical determinism. It has been successfully used to detect abnormalities in biomedical contexts such as speech and ECG signals (Little et al. 2006, 2007).
The RPDE value 
H
n
o
r
m
{\displaystyle \scriptstyle H_{\mathrm {norm} }}
 is a scalar in the range zero to one. For purely<unk> ic signals, 
H
n
o
r
m
=
0
{\displaystyle \scriptstyle H_{\mathrm {norm} }=0}
, whereas for purely i.i.d., uniform white noise, 
H
n
o
r
m
≈
1
{\displaystyle \scriptstyle H_{\mathrm {norm} }\approx 1}
 (Little et al. 2007).
Recurrence period density entropy
Kernel density estimation
Covariance matrix
Arithmetic mean
Algorithms for calculating variance
Quantum yield
Ancillary statistic
ANOVA-simultaneous component analysis