Bayesian sparse vector autoregressive switching models with application to human gesture phase segmentation
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Publication:6616401
DOI10.1214/24-aoas1892MaRDI QIDQ6616401
Unnamed Author, Marina Vannucci, Beniamino Hadj-Amar
Publication date: 9 October 2024
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
- Hidden Markov models with arbitrary state dwell-time distributions
- Joint modeling of multiple time series via the beta process with application to motion capture segmentation
- Strong selection consistency of Bayesian vector autoregressive models based on a pseudo-likelihood approach
- Generating random correlation matrices based on vines and extended onion method
- Multivariate time series modeling and classification via hierarchical VAR mixtures
- Bayesian nonparametric vector autoregressive models
- Optimal predictive model selection.
- Identifying the recurrence of sleep apnea using a harmonic hidden Markov model
- Structural learning of contemporaneous dependencies in graphical VAR models
- Bayesian nonparametric sparse VAR models
- The Bayesian Lasso
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
- Bayesian Model Selection in High-Dimensional Settings
- On Choosing Mixture Components via Non-Local Priors
- Hidden Markov Models for Time Series
- Bayesian approximations to hidden semi-Markov models for telemetric monitoring of physical activity
- Bayesian inference, model selection and likelihood estimation using fast rejection sampling: the Conway-Maxwell-Poisson distribution
- Bayesian inference with the \(l_1\)-ball prior: solving combinatorial problems with exact zeros
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