Strongly consistent code-based identification and order estimation for constrained finite-state model classes

DOI10.1109/18.256497zbMath0784.94005OpenAlexW2097994539MaRDI QIDQ4277148

John Cronan Kieffer

Publication date: 7 February 1994

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/18.256497

zbMATH Keywords

identificationestimationfinite-state sourcesdivergence-rate distancemaximum likelihood codes

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Source coding (94A29)

Related Items (13)

Testing composite hypotheses about discrete ergodic processes ⋮ Relevant states and memory in Markov chain bootstrapping and simulation ⋮ Uniform hypothesis testing for finite-valued stationary processes ⋮ On the minimal penalty for Markov order estimation ⋮ On universal algorithms for classifying and predicting stationary processes ⋮ Approximating multivariate Markov chains for bootstrapping through contiguous partitions ⋮ Theory of Classification: a Survey of Some Recent Advances ⋮ A minimum description length approach to hidden Markov models with Poisson and Gaussian emissions. Application to order identification ⋮ Estimating the order of a hidden markov model ⋮ Consistency of the BIC order estimator ⋮ Number of hidden states and memory: a joint order estimation problem for Markov chains with Markov regime ⋮ The consistency of the BIC Markov order estimator. ⋮ Some remarks on filtering and prediction of stationary processes

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