Model-Based Clustering of Multiple Time Series
Bibliographic Data
| ID | 19418147 |
|---|---|
| Authors | Sylvia Fröhwirth-Schnatter, Sylvia Frühwirth‐Schnatter (0000-0003-0516-5552, Johannes Kepler University of Linz), Sylvia Kaufmann (0000-0003-1918-3321, University of Basel) |
| Year | 2008 |
| Volume | 26 |
| Issue | 1 |
| Pages | 78-89 |
| Publication date | 2008-01-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1198/073500107000000106 |
| OpenAlex | W2071217865 |
| Language | EN |
| Citations received | 12 |
| References cited | 42 |
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 to estimate 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. We discuss model identification and base model selection on marginal likelihoods. A simulation study documents the efficiency gains in estimation and forecasting that are realized when appropriately grouping the time series of a panel. Two economic applications illustrate the usefulness of the method in analyzing also extensions to Markov switching within clusters and heterogeneity within clusters, respectively. JEL classification: C11,C33,E32
Bayesian probability · Cluster analysis · Data mining · Econometrics · Machine learning · Markov chain · Markov chain Monte Carlo · Markov model · Model selection · Pooling · Variable-order Markov model · Complex Systems and Time Series Analysis · Computer Science · Financial Risk and Volatility Modeling · Mathematics · Monetary Policy and Economic Impact · Artificial Intelligence
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| Citations per year | 0.75 |
|---|---|
| Citation span | 2010 - 2023 (14) |
| Highly cited | No |