Sparseness, consistency and model selection for Markov regime-switching Gaussian autoregressive models
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Publication:5037794
DOI10.5705/ss.202019.0190OpenAlexW3205564020MaRDI QIDQ5037794
David A. Stephens, Abbas Khalili
Publication date: 4 March 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202019.0190
EM algorithmautoregressive modelsregularization methodsinformation criteriaMarkov regime-switching models
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Cites Work
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- The Adaptive Lasso and Its Oracle Properties
- Markov-switching model selection using Kullback-Leibler divergence
- On discrete time ergodic filters with wrong initial data
- Covariate selection in mixture models with the censored response variable
- Forgetting the initial distribution for hidden Markov models
- A constrained formulation of maximum-likelihood estimation for normal mixture distributions
- Time series: theory and methods.
- Estimating the dimension of a model
- Heuristics of instability and stabilization in model selection
- Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
- Moments of Markov switching models
- Consistency of the maximum likelihood estimator for general hidden Markov models
- Information criteria and statistical modeling.
- Finite mixture and Markov switching models.
- Joint Determination of the State Dimension and Autoregressive Order for Models with Markov Regime Switching
- Consistent Estimation of Linear and Non-linear Autoregressive Models with Markov Regime
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
- Ideal spatial adaptation by wavelet shrinkage
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- On stability of nonlinear AR processes with Markov switching
- Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime
- Asymptotic Stability of the Optimal Filter with Respect to Its Initial Condition
- On a Mixture Autoregressive Model
- A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
- Stationarity of multivariate Markov-switching ARMA models
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