Implementation of multilayered visualizations for enhanced
    graphical representation of functional analysis data. It combines and integrates
    omics data derived from expression and functional annotation enrichment
    analyses. Its plotting functions have been developed with an hierarchical
    structure in mind: starting from a general overview to identify the most
    enriched categories (modified bar plot, bubble plot) to a more detailed one
    displaying different types of relevant information for the molecules in a given
    set of categories (circle plot, chord plot, cluster plot, Venn diagram, heatmap).

Informal implementation of some algorithms from Graph
  Theory and Combinatorial Optimization which arise in the subject
  "Graphs and Network Optimization" from first course of the EUPLA
  (Escuela Universitaria Politecnica de La Almunia) degree of Data
  Engineering in Industrial Processes.
  References used are:
  Cook et al (1998, ISBN:0-471-55894-X),
  Korte, Vygen (2018) <doi:10.1007/978-3-662-56039-6>,
  Hromkovic (2004) <doi:10.1007/978-3-662-05269-3>,
  Hartmann, Weigt (2005, ISBN:978-3-527-40473-5).

Generalized Odds Rate Mixture Cure (GORMC) model is a flexible model of fitting survival data with a cure fraction, including the Proportional Hazards Mixture Cure (PHMC) model and the Proportional Odds Mixture Cure Model as special cases. This package fit the GORMC model with interval censored data.

Generalized Order-Restricted Information Criterion (GORIC) value for a set of hypotheses in multivariate linear models and generalised linear models.

Implements the generalized order-restricted information criterion
    approximation (GORICA), an AIC-like information criterion that can be
    utilized to evaluate informative hypotheses specifying directional
    relationships between model parameters in terms of (in)equality
    constraints (see Altinisik, Van Lissa, Hoijtink, Oldehinkel, & Kuiper,
    2021), <doi:10.31234/osf.io/t3c8g>. The GORICA is applicable not only to
    normal linear models, but also to generalized linear models (GLMs), 
    generalized linear mixed models (GLMMs), structural equation models
    (SEMs), and contingency tables. For contingency tables, restrictions on cell
    probabilities can be non-linear.