Enables researchers to sample redistricting plans from a pre-specified
    target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo
    algorithms. The package allows for the implementation of various constraints in
    the redistricting process such as geographic compactness and population parity
    requirements. Tools for analysis such as computation of various summary statistics
    and plotting functionality are also included. The package implements the SMC 
    algorithm of McCartan and Imai (2023) <doi:10.1214/23-AOAS1763>, the enumeration 
    algorithm of Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>,
    the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>,
    the Merge-split/Recombination algorithms of Carter et al. (2019) <doi:10.48550/arXiv.1911.01503> 
    and DeFord et al. (2021) <doi:10.1162/99608f92.eb30390f>, and the Short-burst 
    optimization algorithm of Cannon et al. (2020) <doi:10.48550/arXiv.2011.02288>.

Reliable and flexible tools for scoring redistricting plans using 
  common measures and metrics. These functions provide key direct access to 
  tools useful for non-simulation analyses of redistricting plans, such as for 
  measuring compactness or partisan fairness. Tools are designed to work with 
  the 'redist' package seamlessly.

Easy installation, loading, and control of packages for redistricting
    data downloading, spatial data processing, simulation, analysis, and 
    visualization. This package makes it easy to install and load multiple 
    'redistverse' packages at once. The 'redistverse' is developed and maintained 
    by the Algorithm-Assisted Redistricting Methodology (ALARM) Project.
    For more details see <https://alarm-redist.org>.

Provides methods to parse, query and serialize information
    stored in the Resource Description Framework (RDF). RDF is described at <https://www.w3.org/TR/rdf-primer/>.
    This package supports RDF by implementing an R interface to the Redland RDF C library,
    described at <https://librdf.org/docs/api/index.html>. In brief, RDF provides a structured graph
    consisting of Statements composed of Subject, Predicate, and Object Nodes.