Mixture of segmentation for heterogeneous functional data

arXiv:2303.10712v2 Announce Type: replace-cross
Abstract: In this paper we consider functional data with heterogeneity in time and in population. We propose a mixture model with segmentation of time to represent this heterogeneity while keeping the functional structure. Maximum likelihood estimator is considered, proved to be identifiable and consistent. In practice, an EM algorithm is used, combined with dynamic programming for the maximization step, to approximate the maximum likelihood estimator. The method is illustrated on a simulated dataset, and used on …

abstract algorithm arxiv consistent data estimator functional likelihood paper population practice segmentation stat.ap stat.co stat.me stat.ml type