Package: reslr 0.2.0

Maeve Upton

reslr: Modelling Relative Sea Level Data

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.

Authors:Maeve Upton [cph, aut, cre], Andrew Parnell [aut], Niamh Cahill [aut]

reslr_0.2.0.tar.gz
reslr_0.2.0.tar.gz(r-4.7-any)reslr_0.2.0.tar.gz(r-4.6-any)
reslr_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
reslr/json (API)
NEWS

# Install 'reslr' in R:
install.packages('reslr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/maeveupton/reslr/issues

Pkgdown/docs site:https://maeveupton.github.io

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

jagscpp

2.91 score 27 scripts 163 downloads 4 exports 58 dependencies

Last updated from:a3f61e231c. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK271
source / vignettesOK270
linux-release-x86_64OK256
wasm-releaseOK128

Exports:%>%cross_val_checkreslr_loadreslr_mcmc

Dependencies:abindarrayhelpersbackportsbootcheckmateclicodacpp11data.tabledistributionaldotCall64dplyrfarverfastDummiesfieldsgenericsgeosphereggdistggplot2gluegtableisobandlabelinglatticelifecyclemagrittrmapsmatrixStatsncdf4numDerivpillarpkgconfigplyrposteriorpurrrquadprogR2jagsR2WinBUGSR6RColorBrewerRcpprjagsrlangS7scalesspamstringistringrsvUnittensorAtibbletidybayestidyrtidyselectutf8vctrsviridisLitewithr

reslr: advanced

Maeve Upton, Andrew Parnell and Niamh Cahill

Rendered fromadvanced_reslr.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-05-26
Started: 2023-06-15

reslr: quick start guide

Maeve Upton, Andrew Parnell and Niamh Cahill

Rendered fromquick_start.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-05-26
Started: 2023-06-15

reslr: Statistical Models for examining Relative Sea Level Change in R

Maeve Upton, Andrew Parnell & Niamh Cahill

Rendered fromreslr.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-05-26
Started: 2023-06-15