Matrix model used in the state-space formulation, full parameterization of the variance–covariance matrix between model parameters, and regression between the population counts time series.
We consider a set of minimal identification conditions for dynamic factor models. These conditions have economic interpretations and require fewer restrictions than the static factor framework. Under
The use of a finite mixture of normal distributions in model-based clustering allows to capture non-Gaussian data clusters. However, identifying the clusters from the normal components is challenging
