The Bayesian modelling of relative sea-level data using a comprehensive approach that incorporates various statistical models within a unifying framework. Details regarding each statistical models; linear regression (Ashe et al 2019) <doi:10.1016/j.quascirev.2018.10.032>, change point models (Cahill et al 2015) <doi:10.1088/1748-9326/10/8/084002>, integrated Gaussian process models (Cahill et al 2015) <doi:10.1214/15-AOAS824>, temporal splines (Upton et al 2023) <arXiv:2301.09556>, spatio-temporal splines (Upton et al 2023) <arXiv:2301.09556> and generalised additive models (Upton et al 2023) <arXiv:2301.09556>. This package facilitates data loading, model fitting and result summarisation. Notably, it accommodates the inherent measurement errors found in relative sea-level data across multiple dimensions, allowing for their inclusion in the statistical models.
Package details |
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Author | Maeve Upton [cph, aut, cre] (<https://orcid.org/0000-0002-3185-7731>), Andrew Parnell [aut], Niamh Cahill [aut] |
Maintainer | Maeve Upton <uptonmaeve010@gmail.com> |
License | MIT + file LICENSE |
Version | 0.1.1 |
URL | https://github.com/maeveupton/reslr https://maeveupton.github.io/reslr/ |
Package repository | View on CRAN |
Installation |
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