Geospatial data integration framework that merges raster, spatial polygon, and (dynamic) spatial points data into a spatial (panel) data frame at any geographical resolution.

Provides facilities to read, write and validate geographic metadata 
 defined with ISO TC211 / OGC ISO geographic information metadata standards, and 
 encoded using the ISO 19139 (XML) standard technical specification. This includes 
 ISO 19110 (Feature cataloguing), 19115 (dataset metadata), 19119 (service metadata) 
 and 19136 (GML). Other interoperable schemas from the OGC are progressively supported 
 as well, such as the Sensor Web Enablement (SWE) Common Data Model, the OGC GML 
 Coverage Implementation Schema (GMLCOV), or the OGC GML Referenceable Grid (GMLRGRID).

Geometry shapes in 'R' are typically represented by matrices (points, lines), with more complex 
  shapes being lists of matrices (polygons). 'Geometries' will convert various 'R' objects into these shapes. 
  Conversion functions are available at both the 'R' level, and through 'Rcpp'.

Makes the 'Qhull' library <http://www.qhull.org>
    available in R, in a similar manner as in Octave and MATLAB. Qhull
    computes convex hulls, Delaunay triangulations, halfspace
    intersections about a point, Voronoi diagrams, furthest-site
    Delaunay triangulations, and furthest-site Voronoi diagrams. It
    runs in 2D, 3D, 4D, and higher dimensions. It implements the
    Quickhull algorithm for computing the convex hull. Qhull does not
    support constrained Delaunay triangulations, or mesh generation of
    non-convex objects, but the package does include some R functions
    that allow for this.

Simulates from discrete and continuous target distributions 
        using geometric Metropolis-Hastings (MH) 
        algorithms. Users specify the target distribution 
        by an R function that evaluates the log un-normalized pdf or pmf. The package 
        also contains a function implementing a specific geometric MH algorithm for 
        performing high dimensional Bayesian variable selection.