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We compare the two basic ordinal patterns, i.e., the original and amplitude permutations, used to characterize vector structures. The original permutation consists of the indexes of reorganized values in the original vector. By contrast, the amplitude permutation comprises the positions of values in the reordered vector, and it directly reflects the temporal structure. To accurately convey the structural characteristics of vectors, we modify indexes of equal values in permutations to be the same as, for example, the smallest or largest indexes in each group of equalities. Overall, we clarify the relationship between the original and amplitude permutations. And the results have implications for time- and amplitude-symmetric vectors and will lead to further theoretical and experimental studies.
We introduce the Box-Cox symmetric class of distributions, which is useful for modeling positively skewed, possibly heavy-tailed, data. The new class of distributions includes the Box-Cox t, Box-Cox Cole-Gree, Box-Cox power exponential distributions,
A connectome is a map of the structural and/or functional connections in the brain. This information-rich representation has the potential to transform our understanding of the relationship between patterns in brain connectivity and neurological proc
In this paper, we study different discrete data clustering methods, which use the Model-Based Clustering (MBC) framework with the Multinomial distribution. Our study comprises several relevant issues, such as initialization, model estimation and mode
The growing study of time series, especially those related to nonlinear systems, has challenged the methodologies to characterize and classify dynamical structures of a signal. Here we conceive a new diagnostic tool for time series based on the conce
We provide a MATLAB toolbox, BFDA, that implements a Bayesian hierarchical model to smooth multiple functional data with the assumptions of the same underlying Gaussian process distribution, a Gaussian process prior for the mean function, and an Inve