Our CUB statistic uses the concept of entropy, which estimates data regularities based on a combination of order and proportion.
Scientific theories seek to provide simple explanations for significant empirical regularities based on fundamental physical and mechanistic constraints.
Instead of a multiplicative mechanism, we propose here that the observed regularity is based on the Weber and Fechner laws [48, 49].
In both cases internal structural properties of genomes emerge which highlight regularity indicators, based on the number and distribution of repeats.
Three different approaches are now available if one wants to study these stability issues: a first one using symmetrization, another one via mass transportation and a third one based on the regularity theory for minimal surfaces and other PDEs.
We propose a representation of emotion through the parameters of speed, intensity, regularity, and extent, based on the result of our literature review.
Statistical tests for aggregation or regularity are usually based on the comparison of the observed g(d) with confidence envelopes obtained from simulations.
The structural regularity is subsequently evaluated based on the storey capacity factor.
An empirical relationship between the critical drift concentration factor and the overall regularity index is derived based on the dynamic analysis results.
The first two models depend on the Hurst exponent H, and the last one is designed for small data lengths, in which the number of IMFs after EMD is obtained based on the regularity of the signal, and depends on an index measure of regularity.
