IDEAS home Printed from https://ideas.repec.org/r/bes/jnlbes/v26y2008p78-89.html
   My bibliography  Save this item

Model-Based Clustering of Multiple Time Series

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Borja Lafuente-Rego & José A. Vilar, 2016. "Clustering of time series using quantile autocovariances," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(3), pages 391-415, September.
  2. Eduardo Bandrés & María Dolores Gadea-Rivas & Ana Gómez-Loscos, 2017. "Regional business cycles across europe," Occasional Papers 1702, Banco de España;Occasional Papers Homepage.
  3. Frühwirth-Schnatter, Sylvia & Pamminger, Christoph & Weber, Andrea & Winter-Ebmer, Rudolf, 2014. "When Is The Best Time To Give Birth?," Economics Series 308, Institute for Advanced Studies.
  4. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, pages 1682-1700.
  5. Crowley, Patrick M., 2008. "One money, several cycles? : evaluation of European business cycles using model-based cluster analysis," Research Discussion Papers 3/2008, Bank of Finland.
  6. Roberto Casarin & Komla Mawulom Agudze & Monica Billio & Eric Girardin, 2014. "Growth-cycle phases in China�s provinces: A panel Markov-switching approach," Working Papers 2014:19, Department of Economics, University of Venice "Ca' Foscari".
  7. Hernández-Murillo, Rubén & Owyang, Michael T. & Rubio, Margarita, 2017. "Clustered housing cycles," Regional Science and Urban Economics, Elsevier, pages 185-197.
  8. E. Otranto & M. Mucciardi, 2017. "Clustering Space-Time Series: A Flexible STAR Approach," Working Paper CRENoS 201707, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  9. Aßmann, Christian & Boysen-Hogrefe, Jens, 2011. "A Bayesian approach to model-based clustering for binary panel probit models," Computational Statistics & Data Analysis, Elsevier, pages 261-279.
  10. Miguel A. Juárez & Mark F. J. Steel, 2010. "Non‐gaussian dynamic bayesian modelling for panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 1128-1154.
  11. Sylvia Frühwirth‐Schnatter & Christoph Pamminger & Andrea Weber & Rudolf Winter‐Ebmer, 2012. "Labor market entry and earnings dynamics: Bayesian inference using mixtures‐of‐experts Markov chain clustering," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1116-1137, November.
  12. Frühwirth-Schnatter, Sylvia & Pamminger, Christoph & Weber, Andrea & Winter-Ebmer, Rudolf, 2014. "When Is The Best Time To Give Birth - Career Effects Of Early Birth Decisions," CEPR Discussion Papers 10132, C.E.P.R. Discussion Papers.
  13. Sylvia Frühwirth-Schnatter, 2011. "Panel data analysis: a survey on model-based clustering of time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 251-280, December.
  14. Sylvia Kaufmann & Sylvia Frühwirth-Schnatter, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 275-305.
  15. Harvill, Jane L. & Ravishanker, Nalini & Ray, Bonnie K., 2013. "Bispectral-based methods for clustering time series," Computational Statistics & Data Analysis, Elsevier, pages 113-131.
  16. Jacques, Julien & Preda, Cristian, 2014. "Model-based clustering for multivariate functional data," Computational Statistics & Data Analysis, Elsevier, pages 92-106.
  17. De Angelis, Luca & Dias, José G., 2014. "Mining categorical sequences from data using a hybrid clustering method," European Journal of Operational Research, Elsevier, pages 720-730.
  18. Rombouts Jeroen V. K. & Bouaddi Mohammed, 2009. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, pages 1-32.
  19. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, pages 179-195.
  20. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, pages 935-947.
  21. Rombouts Jeroen V. K. & Bouaddi Mohammed, 2009. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, pages 1-32.
  22. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, pages 179-195.
  23. Carmelo J. León & Jorge E. Araña, 2012. "The Dynamics of Preference Elicitation after an Environmental Disaster: Stability and Emotional Load," Land Economics, University of Wisconsin Press, pages 362-381.
  24. De Angelis, L & Paas, L.J., 2009. "The dynamic analysis and prediction of stock markets through the latent Markov model," Serie Research Memoranda 0053, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  25. Rosetta Lombardo & Marianna Falcone, 2011. "Crime And Economic Performance. A Cluster Analysis Of Panel Data On Italy'S Nuts 3 Regions," Working Papers 201112, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
  26. Frühwirth-Schnatter, Sylvia & Pittner, Stefan & Weber, Andrea & Winter-Ebmer, Rudolf, 2016. "Analysing Plant Closure Effects Using Time-Varying Mixture-of-Experts Markov Chain Clustering," Economics Series 324, Institute for Advanced Studies.
  27. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany.
  28. Aßmann, Christian & Boysen-Hogrefe, Jens, 2009. "A bayesian approach to model-based clustering for panel probit models," Economics Working Papers 2009-03, Christian-Albrechts-University of Kiel, Department of Economics.
  29. Alonso, A.M. & Berrendero, J.R. & Hernandez, A. & Justel, A., 2006. "Time series clustering based on forecast densities," Computational Statistics & Data Analysis, Elsevier, pages 762-776.
  30. León, Carmelo J. & Araña, Jorge E. & Hanemann, W. Michael & Riera, Pere, 2014. "Heterogeneity and emotions in the valuation of non-use damages caused by oil spills," Ecological Economics, Elsevier, pages 129-139.
  31. Sylvia Frühwirth-Schnatter & Stefan Pittner & Andrea Weber & Rudolf Winter-Ebmer, 2016. "Analysing Plant Closure Effects Using Time-Varying Mixture-of-Experts Markov Chain Clustering," Economics working papers 2016-10, Department of Economics, Johannes Kepler University Linz, Austria.
  32. repec:eee:csdana:v:113:y:2017:i:c:p:475-496 is not listed on IDEAS
  33. Martin Schneider & Gerhard Fenz, 2011. "Transmission of business cycle shocks between the US and the euro area," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2777-2793.
  34. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  35. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 309-344.
  36. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, pages 935-947.
  37. Sergei Shibaev, 2016. "Recession Propagation in Small Regional Economies: Spatial Spillovers and Endogenous Clustering," Working Papers 1369, Queen's University, Department of Economics.
  38. Christian Aßmann & Jens Boysen-Hogrefe, 2010. "Analysis of current account reversals via regime switching models," Economic Change and Restructuring, Springer, pages 21-43.
  39. Charles Bouveyron & Julien Jacques, 2011. "Model-based clustering of time series in group-specific functional subspaces," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 281-300, December.
  40. repec:onb:oenbwp:y::i:144:b:1 is not listed on IDEAS
  41. Francis, Neville & Owyang, Michael T. & Savascin, Özge, 2012. "An endogenously clustered factor approach to international business cycles," Working Papers 2012-014, Federal Reserve Bank of St. Louis, revised 10 Feb 2017.
  42. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, pages 374-396.
IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.