This package performs 2D Delaunay triangulation, constrained or unconstrained, with the help of the C++ library CDT. A function to plot the triangulation is provided. The constrained Delaunay triangulation has applications in geographic information systems.

This package provides tools for manipulating, exploring, and visualising multiple-response data, including scored or ranked responses. Conversions to and from factors, lists, strings, matrices; reordering, lumping, flattening; set operations; tables; frequency and co-occurrence plots.

Use dynamic programming method to solve l1 convex clustering with identical weights.

Calculate false ring proportions from data frames of intra annual density fluctuations.

Builds statistical control charts with exact limits for univariate and multivariate cases.

This package provides arrays with flexible control over dimension dropping when subscripting.

Likelihood inference based on higher order approximations for linear nonnormal regression models.

Patient Rule Induction Method (PRIM) for bump hunting in high-dimensional data.

To find the certainty of dominance interactions with indirect interactions being considered.

Procrustes analyses to infer co-phylogenetic matching between pairs of phylogenetic trees.

Set of functions for analysis of Principal Coordinates of Phylogenetic Structure (PCPS).

Fits penalized generalized estimating equations to longitudinal data with high-dimensional covariates.

Densitometric evaluation of the photo-archived quantitative thin-layer chromatography (TLC) plates.

This package performs structured OLS (sOLS) and structured SIR (sSIR).

Improve the usage of model fitting functions within a piped work flow.

This package provides tools to normalize (several) Hi-C data from replicates.

Integrative copy number variation (CNV) detection from multiple platform and experimental design.

The package is designed to detect marker genes from RNA-seq data.

This package provides a pure R implementation of the t-SNE algorithm.

This package provides a cross-validated minimal-optimal feature selection algorithm. It utilises popularity counting, hierarchical clustering with feature dissimilarity measures, and prefiltering with all-relevant feature selection method to obtain the minimal-optimal set of features.

This package provides a recursively partitioned mixture model for Beta and Gaussian mixtures. This is a model-based clustering algorithm that returns a hierarchy of classes, similar to hierarchical clustering, but also similar to finite mixture models.

This package provides functions for extracting feature contributions from a random forest model from package randomForest. Feature contributions provide detailed information about the relationship between data variables and the predicted value returned by random forest model.

Pointwise generation and display of attractors (prefractals) of the random iterated function system (RIFS) for various combinations of probabilistic and geometric parameters of some fixed point sets (protofractals), described by Bukhovets A.G. (2012) <doi:10.1134/S0005117912020154>.

Estimates robust rank-based fixed effects and predicts robust random effects in two- and three- level random effects nested models. The methodology is described in Bilgic & Susmann (2013) <https://journal.r-project.org/archive/2013/RJ-2013-027/>.