Converts Between GeoJSON and simple feature objects.

A compilation of tools to complete common tasks for studying gerrymandering. 
    This focuses on the geographic tool side of common problems, such as linking 
    different levels of spatial units or estimating how to break up units. Functions 
    exist for creating redistricting-focused data for the US.

Set of routines for making map projections (forward and inverse), topographic maps, perspective plots, geological maps, geological map symbols, geological databases, interactive plotting and selection of focus regions.

Data sets included here are for use with package GEOmap. These include world map, USA map, Coso map, Japan Map.

Performs Geometrical Archetypal Analysis after creating Grid Archetypes 
    which are the Cartesian Product of all minimum, maximum variable values. Since the archetypes 
    are fixed now, we have the ability to compute the convex composition coefficients for all 
    our available data points much faster by using the half part of Principal Convex Hull Archetypal method. 
    Additionally we can decide to keep as archetypes the closer to the Grid Archetypes ones. Finally 
    the number of archetypes is always 2 to the power of the dimension of our data points 
    if we consider them as a vector space. 
    Cutler, A., Breiman, L. (1994)      <doi:10.1080/00401706.1994.10485840>.
    Morup, M., Hansen, LK. (2012) <doi:10.1016/j.neucom.2011.06.033>.
    Christopoulos, DT. (2024) <doi:10.13140/RG.2.2.14030.88642>.

Tools to easily visualize geographic data of Morocco.
    This package interacts with data available through the
    'geomarocdata' package, which is available in a 'drat' 
    repository.   The size of the 'geomarocdata' package is
    approximately 12 MB.

Provides eigenvector-based (geometric) forecast
    combination methods; also includes simple approaches (simple average,
    median, trimmed and winsorized mean, inverse rank method) and regression-based
    combination. Tools for data pre-processing are available in order to deal with 
    common problems in forecast combination (missingness, collinearity).