Asymptotic analysis of model selection criteria for general hidden Markov models
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Publication:1994901
DOI10.1016/j.spa.2020.10.006zbMath1472.62138arXiv1811.11834OpenAlexW3096602043MaRDI QIDQ1994901
Shouto Yonekura, Alexandros Beskos, Sumeetpal S. Singh
Publication date: 18 February 2021
Published in: Stochastic Processes and their Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1811.11834
Computational methods in Markov chains (60J22) Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Markov processes: estimation; hidden Markov models (62M05) Statistical aspects of information-theoretic topics (62B10)
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Cites Work
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- Particle approximations of the score and observed information matrix in state space models with application to parameter estimation
- The maximizing set of the asymptotic normalized log-likelihood for partially observed Markov chains
- Simulated likelihood inference for stochastic volatility models using continuous particle filtering
- Asymptotic properties of the maximum likelihood estimation in misspecified hidden Markov models
- Hidden Markov models in finance
- Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
- Estimating the dimension of a model
- Risk bounds for model selection via penalization
- Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
- Maximum likelihood principle and model selection when the true model is unspecified
- The consistency of the BIC Markov order estimator.
- Information criteria for selecting possibly misspecified parametric models
- Online expectation maximization based algorithms for inference in hidden Markov models
- Exponential forgetting and geometric ergodicity in hidden Markov models
- Learning the distribution of latent variables in paired comparison models with round-robin scheduling
- Posterior consistency for partially observed Markov models
- Inference in hidden Markov models.
- Consistency of the maximum likelihood estimator for general hidden Markov models
- Mean Field Simulation for Monte Carlo Integration
- Model Selection and Model Averaging
- The Application of Hidden Markov Models in Speech Recognition
- Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation
- A note on composite likelihood inference and model selection
- Regression and time series model selection in small samples
- An optimal selection of regression variables
- Selection of the order of an autoregressive model by Akaike's information criterion
- Generalised information criteria in model selection
- Hidden Markov Models and Disease Mapping
- Optimal error exponents in hidden markov models order estimation
- Bayes Factors
- Analogues of Khintchine, Marcinkiewicz–Zygmund and Rosenthal Inequalities for Symmetric Statistics
- Bridging AIC and BIC: A New Criterion for Autoregression
- The Hartman-Wintner Law of the Iterated Logarithm for Martingales
- A new look at the statistical model identification
