Modelling Relative Sea Level Data R package reslr version 0.2.0 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 2025) <doi:10.32614/RJ-2024-018>, spatio-temporal splines (Upton et al 2025) <doi:10.32614/RJ-2024-018> and generalised additive models (Upton et al 2025) <doi:10.1093/jrsssc/qlae044>. 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. Software 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 Maeve Upton <uptonmaeve010@gmail.com> Comprehensive R Archive Network (CRAN) Maeve Upton [cph, aut, cre] (ORCID: <https://orcid.org/0000-0002-3185-7731>), Andrew Parnell [aut], Niamh Cahill [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=reslr/LICENSE) 2026-05-26 application/tgz https://CRAN.R-project.org/package=reslr doi:10.32614/CRAN.package.reslr en-US