Extending R’s Dendrogram Functionality (dendextend)
Offers a set of functions for extending dendrogram objects in R, letting you visualize and compare trees of hierarchical clusterings. You can (1) Adjust a trees graphical parameters – the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different dendrograms to one another.
Linear Regression by Gibbs Sampling (lrgs)
Implements a Gibbs sampler to do linear regression with multiple covariates, multiple responses, Gaussian measurement errors on covariates and responses, Gaussian intrinsic scatter, and a covariate prior distribution which is given by either a Gaussian mixture of specified size or a Dirichlet process with a Gaussian base distribution.
Tree Boosting for Multivariate Outcomes (mvtboost)
Fits a multivariate model of decision trees for multiple, continuous outcome variables. A model for each outcome variable is fit separately, selecting predictors that explain that explain covariance in multiple outcomes. Package is built on top of ‘gbm’.