Infinite hidden Markov models for cylindrical data

We propose an infinite hidden Markov model for cylindrical time series with von Mises-Gamma emissions. Posterior inference is performed using a beam sampler combining conjugate updates and approximate sampling schemes. Simulation studies and two real data applications demonstrate the effectiveness of the proposed methodology.

Paper

Similar papers

© 2026 NYSGPT2525 LLC