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msarima: Multi-Seasonal ARIMA Models
Fit, forecast and simulate autoregressive integrated moving average (ARIMA) models with more than one seasonal component, following Lisi and Grigoletto (2025) <doi:10.1002/for.3283>. Series observed at high frequency often display several seasonal cycles at once, such as the daily and the weekly pattern of hourly data, which a single seasonal ARIMA operator cannot represent. Estimation is performed by conditional maximum likelihood through numerical optimisation, with support for fixed coefficients and a constant term. Multi-seasonal Ljung-Box and Monti portmanteau tests, following Grigoletto and Lisi (2026) <doi:10.48550/arXiv.2609.32381>, seasonal correlograms, forecasts with prediction intervals, and simulation from a model specification or from a fitted model are also provided.
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Package details |
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| Author | Daniele Girolimetto [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9387-1232>), Francesco Lisi [aut] (ORCID: <https://orcid.org/0000-0002-8749-8889>), Matteo Grigoletto [aut] (ORCID: <https://orcid.org/0000-0001-9881-2039>) |
| Maintainer | Daniele Girolimetto <daniele.girolimetto@unipd.it> |
| License | GPL-3 |
| Version | 0.1.0 |
| URL | https://github.com/danigiro/msarima https://danigiro.github.io/msarima/ |
| Package repository | View on CRAN |
| Installation |
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