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reslr (version 0.1.1)

Modelling Relative Sea Level Data

Description

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) , change point models (Cahill et al 2015) , integrated Gaussian process models (Cahill et al 2015) , temporal splines (Upton et al 2023) , spatio-temporal splines (Upton et al 2023) and generalised additive models (Upton et al 2023) . 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.

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Install

install.packages('reslr')

Monthly Downloads

262

Version

0.1.1

License

MIT + file LICENSE

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Maintainer

Maeve Upton

Last Published

June 15th, 2023

Functions in reslr (0.1.1)

plot.reslr_output

Plotting the results for each statistical model from the reslr_mcmc function.
summary.reslr_output

Produces summaries and convergence diagnostics for an object created with reslr_mcmc.
reslr_load

Loading in data for the reslr package
print.reslr_output

Print a reslr output object which is created by the reslr_mcmc function.
%>%

Pipe operator
cross_val_check

Cross validation check for spline in time, spline in space time and GAM in order to select the most appropriate number of knots when creating basis functions.
reslr_mcmc

Run a reslr_input object through the main reslr Markov chain Monte Carlo (MCMC) function using a chosen statistical model
plot.reslr_input

Plot raw data with measurement uncertainty.
NAACproxydata

Relative Sea level example dataset
print.reslr_input

Print a reslr output object which is created from the reslr_load function.