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Conditional entropy of ordinal patterns
In this paper we investigate a quantity called conditional entropy of ordinal
patterns, akin to the permutation entropy. The conditional entropy of ordinal
patterns describes the average diversity of the ordinal patterns succeeding a
given ordinal pattern. We observe that this quantity provides a good estimation
of the Kolmogorov-Sinai entropy in many cases. In particular, the conditional
entropy of ordinal patterns of a finite order coincides with the
Kolmogorov-Sinai entropy for periodic dynamics and for Markov shifts over a
binary alphabet. Finally, the conditional entropy of ordinal patterns is
computationally simple and thus can be well applied to real-world data
Generalized biodiversity assessment by Bayesian nested random effects models with spyke-and-slab priors
We analyze variations in alpha-diversity of benthic macroinvertebrate communities in an Italian lagoon system using Bayesian hierarchical models with nested random effects. Our aim is to understand how spatial scales influence microhabitat definition. Tsallis entropy measures diversity and spike-and-slab regression selects predictors
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