Summarises a collection of partitions into a single optimal partition. The objective function is the expected posterior loss, and the minimisation is performed through a greedy algorithm described in Rastelli, R. and Friel, N. (2017) "Optimal Bayesian estimators for latent variable cluster models" <DOI:10.1007/s11222-017-9786-y>.

Computes experimental designs for two-arm experiments with
    covariates using multiple methods, including: (0) complete randomization
    and randomization with forced-balance; (1) greedy optimization of a balance
    objective function via pairwise switching; (2) numerical optimization via
    'gurobi'; (3) rerandomization; (4) Karp's method for one covariate; (5)
    exhaustive enumeration for small sample sizes; (6) binary pair matching
    using 'nbpMatching'; (7) binary pair matching plus method (1) to further
    optimize balance; (8) binary pair matching plus method (3) to further
    optimize balance; (9) Hadamard designs; and (10) simultaneous multiple
    kernels. For the greedy, rerandomization, and related methods, three
    objective functions are supported: Mahalanobis distance, standardized sums
    of absolute differences, and kernel distances via the 'kernlab' library.
    This package is the result of a stream of research that can be found in
    Krieger, A. M., Azriel, D. A., and Kapelner, A. (2019). "Nearly Random
    Designs with Greatly Improved Balance." Biometrika 106(3), 695-701
    <doi:10.1093/biomet/asz026>. Krieger, A. M., Azriel, D. A., and
    Kapelner, A. (2023). "Better experimental design by hybridizing binary
    matching with imbalance optimization." Canadian Journal of Statistics,
    51(1), 275-292 <doi:10.1002/cjs.11685>.

These are GreedyExperimentalDesign Java dependency libraries. Note: this package has no functionality of its own and should not be installed as a standalone package without GreedyExperimentalDesign.

An implementation of functions to display Greek letters on the 'RStudio' (include subscript and superscript indexes) and 'RGui' (without subscripts and only with superscript 1, 2 or 3; because 'RGui' doesn't support printing the corresponding Unicode characters as a string: all subscripts ranging from 0 to 9 and superscripts equal to 0, 4, 5, 6, 7, 8 or 9). The functions in this package do not work properly on the R console. Characters are used via Unicode and encoded as UTF-8 to ensure that they can be viewed on all operating systems. Other characters related to mathematics are included, such as the infinity symbol. All this accessible from very simple commands. This is a package that can be used for teaching purposes, the statistical notation for hypothesis testing can be written from this package and so it is possible to build a course from the 'swirlify' package. Another utility of this package is to create new summary functions that contain the functional form of the model adjusted with the Greek letters, thus making the transition from statistical theory to practice easier. In addition, it is a natural extension of the 'clisymbols' package.