Counting forbidden patterns in irregularly sampled time series. I. The effects of under-sampling, random depletion, and timing jitter
M McCullough, K Sakellariou, T Stemler… - … Journal of Nonlinear …, 2016 - pubs.aip.org
It has been established that the count of ordinal patterns, which do not occur in a time series,
called forbidden patterns, is an effective measure for the detection of determinism in noisy
data. A very recent study has shown that this measure is also partially robust against the
effects of irregular sampling. In this paper, we extend said research with an emphasis on
exploring the parameter space for the method's sole parameter—the length of the ordinal
patterns—and find that the measure is more robust to under-sampling and irregular …
called forbidden patterns, is an effective measure for the detection of determinism in noisy
data. A very recent study has shown that this measure is also partially robust against the
effects of irregular sampling. In this paper, we extend said research with an emphasis on
exploring the parameter space for the method's sole parameter—the length of the ordinal
patterns—and find that the measure is more robust to under-sampling and irregular …
