Finite Mixture and Markov Switching Models

Keywords

Markov chain, Computer science, Mathematics, Statistics

References

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• A general maximum likelihood analysis of overdispersion in generalized linear modelsMurray Aitkin — 1996
• Calculating posterior distributions and modal estimates in Markov mixture modelsSiddhartha Chib — 1996
• Estimating Marginal Likelihoods for Mixture and Markov Switching Models Using Bridge Sampling TechniquesSylvia Frühwirth‐Schnatter — 2004
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business CycleJames D. Hamilton — 1989
• Bayesian Treatment of the Independent Student- t Linear ModelJohn Geweke — 1993
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• STATISTICAL ANALYSIS OF ECONOMIC TIME SERIES VIA MARKOV SWITCHING MODELSRobert E. McCulloch, Ruey S. Tsay — 1994
• Bayesian Analysis of Poisson MixturesValérie Viallefont, Sylvia Richardson, Peter J. Green — 2002
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Cited by

• Political Participation is More than Just Resources: A New Approach to the Study of Civic EngagementInés Levin, Michael Alvarez, D. Roderick Kiewiet — 2011
• The Consequences of an Unknown Debt TargetAlexander W. Richter, Nathaniel A. Throckmorton — 2015
• Robust REML estimation for k‐component Poisson mixture with random effects: application to the epilepsy seizure count data and urinary tract infections dataDorothy W. Jackson — 2013
• Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models隆照 岡安 — 2017
• From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clusteringJuan Manuel Alonso Furelos — 2018
• Probabilistic scenario-based decision making for water resources planning and managementC. Dong — 2014
• Decoding the Structural Layer of Transcriptional Regulation : Computational Analyses of Chromatin and Chromosomal AberrationsRobin Andersson — 2010
• Finite Mixture Models in Market Segmentation: A Review and Suggestions for Best PracticesMichael Nche Tuma, Reinhold Decker — 2013
• Markov and semi-Markov switching linear mixed models for identifying forest tree growth components.Florence Chaubert‐Pereira, Yann Guédon, Christian Lavergne — 2008
• FlexMix: An R package for finite mixture modellingBettina Grün, Friedrich Leisch — 2007
• Clustering of gene expression data via normal mixture models.Geoffrey J. McLachlan, L.K. Flack, Shu‐Kay Ng — 2013
• Clustering using skewed multivariate heavy tailed distributions with flexible tail behaviourDarren Wraith, Florence Forbes — 2014
• Fault detection in complex and distributed systemsDejan P. Jovanović — 2014
• Comparison of Mixture and Classification Maximum Likelihood Approaches in Poisson Regression ModelsSusana Faria, Gilda Soromenho — 2008
• Bayesian Modeling of Conditional DensitiesFeng Li — 2013
• Estimating a MS-TVTP Model with Matlab SoftwareKnani Ramzi — 2012
• Essays on Bayesian Analysis of Time Varying Economic PatternsPinar Ceyhan — 2010
• Latent variable models in statistical geneticsChristopher Oldmeadow — 2009
• Financial Implications of Extreme and Rare EventsLorán Chollete, Dwight M. Jaffee — 2009
• Markov-Switching Vector Autoregressive Models: Monte Carlo experiment, impulse response analysis, and Granger-Causal analysisMatthieu Droumaguet — 2012

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