Exact and approximate hidden Markov chain filters based on discrete observations

DOI10.1515/strm-2015-0004zbMath1339.60040arXiv1411.0849OpenAlexW1758341678MaRDI QIDQ293595

Nicole Bäuerle, Igor Gilitschenski, Uwe D. Hanebeck

Publication date: 9 June 2016

Published in: Statistics \& Risk Modeling (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.0849

zbMATH Keywords

Brownian motionhidden Markov modelcontinuous-time Markov chainWonham filterasymmetric telegraph processdiscrete Bayesian filter

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Inference from stochastic processes and prediction (62M20) Probabilistic models, generic numerical methods in probability and statistics (65C20) Brownian motion (60J65) Signal detection and filtering (aspects of stochastic processes) (60G35) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical analysis or methods applied to Markov chains (65C40) Continuous-time Markov processes on discrete state spaces (60J27)

Related Items (1)

\(\mathcal{L}_1 \)-optimal filtering of Markov jump processes. I: Exact solution and numerical implementation schemes

Cites Work

• Markov decision processes with applications to finance.
• An EM algorithm for estimation in Markov-modulated Poisson processes
• A generalized multi-period mean-variance portfolio optimization with Markov switching parameters
• Sequential tracking of a hidden Markov chain using point process observations
• A stochastic model related to the telegrapher's equation
• Optimizing the terminal wealth under partial information: the drift process as a continuous time Markov chain
• Portfolio Selection in the Enlarged Markovian Regime-Switching Market
• Analysis of separable Markov-modulated rate models for information-handling systems
• A Method for the Spatial Discretization of Parabolic Equations in One Space Variable
• Moment based regression algorithms for drift and volatility estimation in continuous-time Markov switching models
• Testing for two states in a hidden Markov model
• Estimation of noisy telegraph processes: Nonlinear filtering versus nonlinear smoothing (Corresp.)
• A second-order Markov-modulated fluid queue with linear service rate
• A NONPARAMETRIC BAYESIAN APPROACH TO DETECT THE NUMBER OF REGIMES IN MARKOV SWITCHING MODELS
• The Relaxed Investor with Partial Information
• On the Asymmetric Telegraph Processes
• Markowitz's Mean-Variance Portfolio Selection With Regime Switching: From Discrete-Time Models to Their Continuous-Time Limits
• Portfolio Optimization With Markov-Modulated Stock Prices and Interest Rates
• PORTFOLIO OPTIMIZATION UNDER PARTIAL INFORMATION WITH EXPERT OPINIONS
• Estimation for the discretely observed telegraph process
• Portfolio optimization with unobservable Markov-modulated drift process
• Statistical analysis of the inhomogeneous telegrapher's process
• Fully Bayesian analysis of switching Gaussian state space models
• Optimal portfolio policies under bounded expected loss and partial information
• Parameter estimation in continuous time Markov switching models: a semi-continuous Markov chain Monte Carlo approach
• Estimating models based on Markov jump processes given fragmented observation series
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Exact and approximate hidden Markov chain filters based on discrete observations