Implements DB-TARF (Design-Based Targeted Adaptive Residual
    Forest) for large-scale digital soil and ecological mapping evaluated
    under the design-based paradigm of Wadoux et al. (2021)
    <doi:10.1016/j.ecolmodel.2021.109692>. A random forest is augmented by a
    cross-fitted, out-of-fold-selected residual correction (residual forests,
    ordinary kriging, recalibration), together with design-based conformal
    prediction intervals.

Create a wide range of interactive, zoomable vector maps. This
    package is an 'R' binding for the 'geoviz' 'JavaScript' library
    <https://github.com/riatelab/geoviz/>, itself based on the 'd3.js'
    ecosystem <doi:10.1109/TVCG.2011.185>. Like the original 'JavaScript'
    library, the package takes advantage of the many features provided
    by 'd3.js': proportional symbols, pictograms, typologies, choropleth maps,
    spikes, tiles, Dorling cartograms, and more. It can also be used to
    create pretty static vectorial maps in 'svg' format, suitable for
    editorial cartography.

Simulation, estimation and testing for geopolitical volatility (GEOVOL) based on the global common volatility model of Engle and Campos-Martins (2023) <doi:10.1016/j.jfineco.2022.09.009>. GEOVOL is modelled as a latent multiplicative volatility factor with heterogeneous factor loadings. Estimation is carried out as a maximization-maximization procedure, where GEOVOL and the GEOVOL loadings are estimated iteratively until convergence.

Contains the development of a tool that provides a web-based
    graphical user interface (GUI) to perform Techniques from a subset of
    spatial statistics known as geographically weighted (GW) models.
    Contains methods described by Brunsdon et al., 1996
    <doi:10.1111/j.1538-4632.1996.tb00936.x>, Brunsdon et al., 2002
    <doi:10.1016/s0198-9715(01)00009-6>, Harris et al., 2011
    <doi:10.1080/13658816.2011.554838>, Brunsdon et al., 2007
    <doi:10.1111/j.1538-4632.2007.00709.x>.

Large-scale gridded data stores are increasingly using the Zarr 
    format. GeoZarr is defined in terms of a number of community conventions
    built on top of the Zarr specification. These conventions specify how Zarr
    metadata is to be interpreted to attach semantic meaning to the data in the 
    Zarr array providing the metadata. This package implements a number of 
    community conventions on top of the 'zarr' package, enabling the R community 
    to use geospatial data stored in Zarr.