Maximum likelihood estimation of bivariate circular hidden Markov models from incomplete data

DOI10.1080/00949655.2012.656642zbMath1431.62343OpenAlexW2025229611WikidataQ58205251 ScholiaQ58205251MaRDI QIDQ5218862

Francesco Lagona, Marco Picone

Publication date: 6 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.656642

zbMATH Keywords

EM algorithmimportance samplinghidden Markov modelmixturesmissing valuesbivariate circular datasine modelbivariate von Mises

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Markov processes: estimation; hidden Markov models (62M05)

Related Items (3)

Recent advances in directional statistics ⋮ How to test the missing data mechanism in a hidden Markov model ⋮ A hidden Markov model for the analysis of cylindrical time series

Cites Work

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• Dependent models for observations which include angular ones
• Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
• A multivariate von mises distribution with applications to bioinformatics
• Probabilistic model for two dependent circular variables
• Model-based clustering of multivariate skew data with circular components and missing values
• Protein Bioinformatics and Mixtures of Bivariate von Mises Distributions for Angular Data

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