Analysing plant closure effects using time-varying mixture-of-experts Markov chain clustering
From MaRDI portal
Publication:1621035
DOI10.1214/17-AOAS1132zbMath1405.62239MaRDI QIDQ1621035
Andrea Weber, Stefan Pittner, Sylvia Frühwirth-Schnatter, Rudolf Winter-Ebmer
Publication date: 15 November 2018
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aoas/1536652975
clusteringMarkov chain Monte Carlopanel datainhomogeneous Markov chainstransition datamultinomial logit
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to social sciences (62P25) Markov processes: hypothesis testing (62M02)
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Cites Work
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- Model-based clustering of categorical time series
- Estimating the returns to community college schooling for displaced workers
- Mixture of latent trait analyzers for model-based clustering of categorical data
- Hidden Markov models for alcoholism treatment trial data
- A mixture of experts model for rank data with applications in election studies
- Panel data analysis: a survey on model-based clustering of time series
- Finite mixture and Markov switching models.
- Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-tDistributions
- Model‐based clustering of longitudinal data
- Model-Based Gaussian and Non-Gaussian Clustering
- Bayesian Inference in Mixtures-of-Experts and Hierarchical Mixtures-of-Experts Models With an Application to Speech Recognition
- Model-Based Clustering, Discriminant Analysis, and Density Estimation
- Mixed Hidden Markov Models
- Estimation in the Mixture of Markov Chains Moving With Different Speeds
- Bayesian clustering by dynamics