Time Series Clustering with an EM algorithm for Mixtures of Linear Gaussian State Space Models. (arXiv:2208.11907v1 [cs.LG])

In this paper, we consider the task of clustering a set of individual time
series while modeling each cluster, that is, model-based time series
clustering. The task requires a parametric model with sufficient flexibility to
describe the dynamics in various time series. To address this problem, we
propose a novel model-based time series clustering method with mixtures of
linear Gaussian state space models, which have high flexibility. The proposed
method uses a new expectation-maximization algorithm for the mixture model to …

algorithm arxiv clustering lg linear series space state time time series