Bundles the datasets and functions featured in Philip H. 
    Pollock and Barry C. Edwards<https://edge.sagepub.com/pollock>, "An R Companion to Political Analysis, 3rd Edition," Thousand Oaks, CA: Sage Publications.

R interface to CPLEX solvers for linear, quadratic, and (linear and quadratic) mixed integer programs. Support for quadratically constrained programming is available. See the file "INSTALL" for details on how to install the Rcplex package in Linux/Unix-like and Windows systems. Support for sparse matrices is provided by an S3-style class "simple_triplet_matrix" from package slam and by objects from the Matrix package class hierarchy.

The 'Rcpp' package provides R functions as well as C++ classes which
 offer a seamless integration of R and C++. Many R data types and objects can be
 mapped back and forth to C++ equivalents which facilitates both writing of new
 code as well as easier integration of third-party libraries. Documentation
 about 'Rcpp' is provided by several vignettes included in this package, via the
 'Rcpp Gallery' site at <https://gallery.rcpp.org>, the paper by Eddelbuettel and
 Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel (2013,
 <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and Balamuta (2018,
 <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")' for details.

Rcpp11 includes a header only C++11 library that facilitates 
  integration between R and modern C++.

Provides optimized functions and flexible iterators implemented in
    C++ for solving problems in combinatorics and computational mathematics.
    Handles various combinatorial objects including combinations, permutations,
    integer partitions and compositions, Cartesian products, unordered
    Cartesian products, and partition of groups. Utilizes the RMatrix class
    from 'RcppParallel' for thread safety. The combination and permutation
    functions contain constraint parameters that allow for generation of all
    results of a vector meeting specific criteria (e.g. finding all
    combinations such that the sum is between two bounds). Capable of
    ranking/unranking combinatorial objects efficiently (e.g. retrieve only the
    nth lexicographical result) which sets up nicely for parallelization as
    well as random sampling. Gmp support permits exploration where the total
    number of results is large (e.g. comboSample(10000, 500, n = 4)).
    Additionally, there are several high performance number theoretic
    functions that are useful for problems common in computational mathematics.
    Some of these functions make use of the fast integer division library
    'libdivide'. The primeSieve function is based on the segmented sieve of
    Eratosthenes implementation by Kim Walisch. It is also efficient for large
    numbers by using the cache friendly improvements originally developed by
    Tomás Oliveira. Finally, there is a prime counting function that implements
    Legendre's formula based on the work of Kim Walisch.