Apply Two Fuzzy Numbers on a Monotone Function (FuzzyNumbers.Ext.2)
One can easily draw the membership function of f(x,y) by package ‘FuzzyNumbers.Ext.2’ in which f(.,.) is supposed monotone and x and y are two fuzzy numbers. This work is possible using function f2apply() which is an extension of function fapply() from Package ‘FuzzyNumbers’ for two-variable monotone functions.

Create Interactive Collapsible Trees with the JavaScript ‘D3’ Library (d3Tree)
Create and customize interactive collapsible ‘D3’ trees using the ‘D3’ JavaScript library and the ‘htmlwidgets’ package. These trees can be used directly from the R console, from ‘RStudio’, in Shiny apps and R Markdown documents. When in Shiny the tree layout is observed by the server and can be used as a reactive filter of structured data.

Reinforcement Learning Trees (RLT)
Random forest with a variety of additional features for regression, classification and survival analysis. The features include: parallel computing with OpenMP, embedded model for selecting the splitting variable (based on Zhu, Zeng & Kosorok, 2015), subject weight, variable weight, tracking subjects used in each tree, etc.

Automatic Description of Factorial Analysis (FactoInvestigate)
Brings a set of tools to help and automatically realise the description of principal component analyses (from ‘FactoMineR’ functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).

Linear Splines with Convenient Parametrisations (lspline)
Linear splines with convenient parametrisations such that (1) coefficients are slopes of consecutive segments or (2) coefficients are slope changes at consecutive knots. Knots can be set manually or at break points of equal-frequency or equal-width intervals covering the range of ‘x’. The implementation follows Greene (2003), chapter 7.2.5.

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