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) <doi:10.48550/arXiv.2301.09556>, spatio-temporal splines (Upton et al 2023) <doi:10.48550/arXiv.2301.09556> and generalised additive models (Upton et al 2023) <doi:10.48550/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.">

reslr: Modelling Relative Sea Level Data (original) (raw)

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) <doi:10.48550/arXiv.2301.09556>, spatio-temporal splines (Upton et al 2023) <doi:10.48550/arXiv.2301.09556> and generalised additive models (Upton et al 2023) <doi:10.48550/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.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: data.table, dplyr, fastDummies, fields, geosphere, ggplot2, magrittr, ncdf4, plyr, posterior, purrr, R2jags, stringr, tidybayes, tidyr
Suggests: knitr, rmarkdown, testthat, vdiffr
Published: 2023-06-15
DOI: 10.32614/CRAN.package.reslr
Author: Maeve Upton ORCID iD [cph, aut, cre], Andrew Parnell [aut], Niamh Cahill [aut]
Maintainer: Maeve Upton
BugReports: https://github.com/maeveupton/reslr/issues
License: MIT + file
URL: https://github.com/maeveupton/reslr,https://maeveupton.github.io/reslr/
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: reslr results

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