Bayesian cluster analysis for registration and clustering homogeneous subgroups in multidimensional functional data

Anis Fradi and Chafik Samir

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 7, 2242-2258

Abstract: We introduce a new statistical model for clustering populations of functions and multidimensional curves where the domain is a real interval I. We consider that we are given a finite set of observations from a population of curves or functions with values in Rd, for a fixed d≥1 and arguments in I. We are interested in the population background where the clustering is the process of grouping curves into homogeneous sub-populations. In particular, we define a distribution function for each sub-population and use the statistical geometry of the the space of smooth densities to explore a Bayesian model with a spherical Gaussian process prior. We also give the expression of the log-posterior distribution on coefficients resulting from the expansion. Finally, the practical interest of the proposed method is illustrated on simulated and real datasets of multidimensional curves.

Date: 2022
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DOI: 10.1080/03610926.2020.1772979

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