This package provides a robust Partial Least-Squares (PLS) method is implemented that is robust to outliers in the residuals as well as to leverage points. A specific weighting scheme is applied which avoids iterations, and leads to a highly efficient robust PLS estimator.

This package provides a collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.

NChannelSet for rat hepatocytes treated with Carbon Tetrachloride (CCl4) data from LGC company.

Modified quantile normalization for omics or other matrix-like data distorted in location and scale.

This package finds optimal sets of genes that seperate samples into two or more classes.

This package provides tools for clustering and principal component analysis (with robust methods, and parallelized functions).

This package provides a comprehensive collection of color palettes, color maps, and tools to evaluate them.

This is a package providing tools for weighted k-Nearest neighbors for classification, regression and clustering.

Rakudo is a compiler that implements the Raku specification and runs on top of several virtual machines.

This package provides a Tool for Semi-Automating the Statistical Disclosure Control of Research Outputs.

Parameter estimation, one-step ahead forecast and new location prediction methods for spatio-temporal data.

Generates visualizations with Dukeâ s official suite of colors in a color blind friendly way.

This package provides functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.

This package provides functions and a graphical user interface for graphical described multiple test procedures.

This package implements likelihood inference based on higher order approximations for linear nonnormal regression models.

Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.

This package provides a variety of functions useful for data analysis, selection, manipulation, and graphics.

Inference and visualize gene regulatory network based on single-cell RNA sequencing pseudo-time information.

An implementation of the pediatric complex chronic conditions (CCC) classification system using R and C++.

This package provides functions and Datasets from Lohr, S. (1999), Sampling: Design and Analysis, Duxbury.

The sparse principal component regression is computed. The regularization parameters are optimized by cross-validation.

Statistical interpretation of forensic glass transfer (Simulation of the probability distribution of recovered glass fragments).

This package implements Python-style zip for R. Is a more flexible version of cbind.

Selects one model with variable selection FDR controlled at a specified level. A q-value for each potential variable is also returned. The input, variable selection counts over many bootstraps for several levels of penalization, is modeled as coming from a beta-binomial mixture distribution.