**Maximum Diversity Weighting** (**mdw**)

Dimension-reduction methods aim at defining a score that maximizes signal diversity. Two approaches, namely maximum entropy weights and maximum variance weights, are provided.

**Causal Learning of Mixed Graphical Models** (**causalMGM**)

Allows users to learn undirected and directed (causal) graphs over mixed data types (i.e., continuous and discrete variables). To learn a directed graph over mixed data, it first calculates the undirected graph (Sedgewick et al, 2016) and then it uses local search strategies to prune-and-orient this graph (Sedgewick et al, 2017). AJ Sedgewick, I Shi, RM Donovan, PV Benos (2016) <doi:10.1186/s12859-016-1039-0>. AJ Sedgewick, JD Ramsey, P Spirtes, C Glymour, PV Benos (2017) <arXiv:1704.02621>.

**Rendering Word Documents with R Inline Code** (**WordR**)

Serves for rendering MS Word documents with R inline code and inserting tables and plots.

**Semiparametric Regression on Cumulative Incidence Function with Interval-Censored Competing Risks Data** (**intccr**)

The function ciregic() fits semiparametric competing risks regression models with interval-censored data as described in Bakoyannis, Yu, and Yiannoutsos (2017) <doi:10.1002/sim.7350>.

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