Provides a 'dibble' that implements data cubes (derived from 
    'dimensional tibble'), and allows broadcasting by dimensional names.

This package provides utilities to calculate the probabilities of various dice-rolling events, such as the probability of rolling a four-sided die six times and getting a 4, a 3, and either a 1 or 2 among the six rolls (in any order); the probability of rolling two six-sided dice three times and getting a 10 on the first roll, followed by a 4 on the second roll, followed by anything but a 7 on the third roll; or the probabilities of each possible sum of rolling five six-sided dice, dropping the lowest two rolls, and summing the remaining dice.

Space-Filling Designs and space-filling criteria (distance-based and uniformity-based), with emphasis to computer experiments; <doi:10.18637/jss.v065.i11>.

Estimation, validation and prediction of models of different types : linear models, additive models, MARS,PolyMARS and Kriging.

Estimation, validation and prediction of kriging models. Important functions : km, print.km, plot.km, predict.km.

Efficient Global Optimization (EGO) algorithm as described in "Roustant et al. (2012)" <doi:10.18637/jss.v051.i01> and adaptations for problems with noise ("Picheny and Ginsbourger, 2012") <doi:10.1016/j.csda.2013.03.018>, parallel infill, and problems with constraints.

Easy visualization for datasets with more than two categorical variables and additional continuous variables. The package is particularly useful for exploring complex categorical data in the context of pathway analysis across multiple conditions. This package is now in maintenance-only mode and kept for legacy compatibility; for new projects and active development, please use the successor package 'ggdiceplot' (see <https://github.com/maflot/ggdiceplot> and <https://dice-and-domino-plot.readthedocs.io/en/latest/>).

Performs semi-supervised deconvolution of bulk RNA sequencing
    (RNA-seq) data. Known cell-type proportions are estimated using
    supervised methods -- 'CIBERSORTx' (CSx), 'CIBERSORT' (CS), 'FARDEEP' (Fast
    And Robust DEconvolution of Expression Profiles), and 'DCQ' (Digital
    Cell Quantifier) -- while unknown components are inferred using
    non-negative matrix factorization ('NMF') with limited-memory
    Broyden-Fletcher-Goldfarb-Shanno with bounds ('L-BFGS-B') optimization.
    Hyperparameters are selected automatically using a Pareto-frontier-based
    approach with knee-point detection, allowing application when the
    reference signature matrix is incomplete. More details about 'DICEpro' can 
    be found in Ba et al. (2026) <doi:10.64898/2026.06.17.732876>.