Authors@R: c(person("Antonio", "D'Ambrosio", role = c("aut", "cre"), email = "antdambr@unina.it"), person("Sonia", "Amodio", role = "ctb"), person("Giulio", "Mazzeo", role = "ctb"))
Imports: rlist (>= 0.4.2), methods, proxy, gtools
The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties.
This release declare as deprecated some functions that are still in the package for compatibility. Next release will not contains these functions.

Title: Classification and Clustering of Preference Rankings
Authors@R: c(person("Antonio", "D'Ambrosio", role = c("aut", "cre"), email = "antdambr@unina.it"))
Imports: janitor, methods, pracma, rlist, proxy
Description: Tree-based classification and soft-clustering method for preference rankings, with tools for external validation of fuzzy clustering.
It contains the recursive partitioning algorithm for preference rankings, non-parametric tree-based method for a matrix of preference rankings as a response variable. It contains also the distribution-free soft clustering method for preference rankings, namely the K-median cluster component analysis (CCA).
The package depends on the 'ConsRank' R package.
Options for validate the tree-based method are both test-set procedure and V-fold cross validation.
The package contains the routines to compute the adjusted concordance index (a fuzzy version of the adjusted rand index) and the normalized degree of concordance (the corresponding fuzzy version of the rand index).
D'Ambrosio, A., Amodio, S., Iorio, C., Pandolfo, G., and Siciliano, R. (2021) <doi:10.1007/s00357-020-09367-0>
Hullermeier, E., Rifqi, M., Henzgen, S., and Senge, R. (2012) <doi:10.1109/TFUZZ.2011.2179303>.

Title: Fits Regression & ARMA Models Subject to Constraints to the
Description: Fits or generalized linear models either a regression with Autoregressive moving-average (ARMA) errors for time series data.
The package makes it easy to incorporate constraints into the model's coefficients.
The model is specified by an objective function (Gaussian, Binomial or Poisson) or an ARMA order (p,q),
for the coefficients (i.e beta1 > 0) and the possibility to incorporate restrictions
The references of this packages are the same as 'stats' package for glm() and arima() functions.
For the different optimizers implemented, it is recommended to consult the documentation of the corresponding packages.
Imports: data.table (>= 1.10), forecast (>= 8.0), rlang (>= 0.4),