Model‐based clustering for spatiotemporal data on air quality monitoring

Data extracted from air quality monitoring can require spatiotemporal clustering techniques. Of late, many clustering techniques are based on mixture models; however, there is a shortage of model‐based approaches for spatiotemporal data. A new mixture to cluster spatiotemporal data, named STM, is introduced, and generic identifiability is proved. The resulting model defines each mixture component as a mixture of autoregressive polynomial …