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

Compress local and online images using the 'reSmush.it' API
    service <https://resmush.it/>.

Utility functions to download data from the 'RESOURCECODE'
    hindcast database of sea-states, time series of sea-state parameters
    and time series of 1D and 2D wave spectra.  See
    <https://resourcecode.ifremer.fr> for more details about the available
    data.  Also provides facilities to plot and analyse downloaded data,
    such as computing the sea-state parameters from both the 1D and 2D
    surface elevation variance spectral density.

Includes Resourcecode hindcast database (see
    <https://resourcecode.ifremer.fr>) configuration data: nodes locations
    for both the sea-state parameters and the spectra data; examples of
    time series of 1D and 2D surface elevation variance spectral density.

A resource represents some data or a computation unit. It is 
    described by a URL and credentials. This package proposes a Resource model
    with "resolver" and "client" classes to facilitate the access and the usage of the 
    resources.

Resource Selection (Probability) Functions
  for use-availability wildlife data
  based on weighted distributions as described in
  Lele and Keim (2006) <doi:10.1890/0012-9658(2006)87%5B3021:WDAEOR%5D2.0.CO;2>,
  Lele (2009) <doi:10.2193/2007-535>,
  and Solymos & Lele (2016) <doi:10.1111/2041-210X.12432>.