mixture modelling

Model-based Clustering of Multiple Time Series

JEL codes: 
C11, C33, E32
Version Date: 
Aug 2004

We propose to use the attractiveness of pooling relatively short time series that display similar dynamics, but without restricting to pooling all into one group. We suggest estimating the appropriate grouping of time series simultaneously along with the group-specific model parameters. We cast estimation into the Bayesian framework and use Markov chain Monte Carlo simulation methods.

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