arbiter
JournalsPricingAccount

Bayesian multivariate semi-Markov-switching mixed data sampling

Alfonso Russo et al.

Statistical Modelling2025https://doi.org/10.1177/1471082x251395447article
ABDC B
Weight
0.37

What the paper says

We introduce a flexible model for multivariate time-series exhibiting heterogeneous sampling frequencies, where time-varying unobservable heterogeneity is captured by a finite number of latent regimes. The latent unobservable process evolves over time according to a semi-Markov chain. The inference is based on a Bayesian approach involving reversible jump Markov chain Monte Carlo (RJ-MCMC), which allows us to avoid specifying the number of latent regimes in advance. In a simulation study we show how our approach correctly recovers the true configuration of latent regimes with high probability, and that the proposed model can be seen as advantageous with respect to possible competitors. We illustrate through an analysis of two major polluting agents recorded daily at the Danmarksplass site (Norway) in 2022, and their association with certain mixed-frequency weather variables.

1 citation

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1177/1471082x251395447

Or copy a formatted citation

@article{alfonso2025,
  title        = {{Bayesian multivariate semi-Markov-switching mixed data sampling}},
  author       = {Alfonso Russo et al.},
  journal      = {Statistical Modelling},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/1471082x251395447},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Bayesian multivariate semi-Markov-switching mixed data sampling

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.