Nonparametric identification and maximum likelihood estimation for hidden Markov models

DOI10.1093/biomet/asw001zbMath1499.62285arXiv1404.4210OpenAlexW2237093876WikidataQ50630657 ScholiaQ50630657MaRDI QIDQ5384381

No author found.

Publication date: 24 June 2019

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1404.4210

zbMATH Keywords

hidden Markov modelnonparametric identificationnonparametric maximum likelihood estimationlatent state model

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (10)

Unnamed Item ⋮ Spline‐based nonparametric inference in general state‐switching models ⋮ Statistical inference for the nonparametric and semiparametric hidden Markov model via the composite likelihood approach ⋮ Consistent order estimation for nonparametric hidden Markov models ⋮ Hierarchical Markov-switching models for multivariate integer-valued time-series ⋮ Penalized estimation of flexible hidden Markov models for time series of counts ⋮ Nonasymptotic control of the MLE for misspecified nonparametric hidden Markov models ⋮ Kernel-based hidden Markov conditional densities ⋮ Consistency of the maximum likelihood estimator in seasonal hidden Markov models ⋮ A two-step estimator for generalized linear models for longitudinal data with time-varying measurement error

This page was built for publication: Nonparametric identification and maximum likelihood estimation for hidden Markov models