TY - JOUR
T1 - reslr
T2 - An R Package for Relative Sea Level Modelling
AU - Upton, Maeve
AU - Parnell, Andrew
AU - Cahill, Niamh
N1 - Publisher Copyright:
© (2024), (Technische Universitaet Wien). All rights reserved.
PY - 2024
Y1 - 2024
N2 - We present reslr, an R package to perform Bayesian modelling of relative sea level data. We include a variety of different statistical models previously proposed in the literature, with a unifying framework for loading data, fitting models, and summarising the results. Relative sea-level data often contain measurement error in multiple dimensions, and so our package allows for these to be included in the statistical models. When plotting the output sea level curves, the focus is often on comparing rates of change, and so our package allows for computation of the derivatives of sea level curves with appropriate consideration of the uncertainty. We provide a large example dataset from the Atlantic coast of North America and show some of the results that might be obtained from our package.
AB - We present reslr, an R package to perform Bayesian modelling of relative sea level data. We include a variety of different statistical models previously proposed in the literature, with a unifying framework for loading data, fitting models, and summarising the results. Relative sea-level data often contain measurement error in multiple dimensions, and so our package allows for these to be included in the statistical models. When plotting the output sea level curves, the focus is often on comparing rates of change, and so our package allows for computation of the derivatives of sea level curves with appropriate consideration of the uncertainty. We provide a large example dataset from the Atlantic coast of North America and show some of the results that might be obtained from our package.
UR - https://www.scopus.com/pages/publications/105008671836
U2 - 10.32614/RJ-2024-018
DO - 10.32614/RJ-2024-018
M3 - Article
AN - SCOPUS:105008671836
SN - 2073-4859
VL - 16
SP - 61
EP - 81
JO - R Journal
JF - R Journal
IS - 2
ER -