This package provides tools to perform random forest consensus clustering of different data types. The package is designed to accept a list of matrices from different assays, typically from high-throughput molecular profiling so that class discovery may be jointly performed. For references, please see Tao Shi & Steve Horvath (2006) <doi:10.1198/106186006X94072> & Monti et al (2003) <doi:10.1023/A:1023949509487> .

Insert/extract text "reminders" into/from function source code comments or as the "comment" attribute of any object. The former can be handy in development as reminders of e.g. argument requirements, expected objects in the calling environment, required options settings, etc. The latter can be used to provide information of the object and as simple manual "tooltips" for users, among other things.

NCL (NCAR Command Language) is one of the most popular spatial data mapping tools in meteorology studies, due to its beautiful output figures with plenty of color palettes designed by experts <https://www.ncl.ucar.edu/index.shtml>. Here we translate all NCL color palettes into R hexadecimal RGB colors and provide color selection function, which will help users make a beautiful figure.

This package implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The rdlearn package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.

Algorithms for solving a self-calibrated l1-regularized quadratic programming problem without parameter tuning. The algorithm, called DECODE, can handle high-dimensional data without cross-validation. It is found useful in high dimensional portfolio selection (see Pun (2018) <https://ssrn.com/abstract=3179569>) and large precision matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja (2019) <https://ssrn.com/abstract=3422590>).

This package provides tools to find the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees. The distance is computed using the L1 (Manhattan, taxicab) metric.

This package provides a client library for making requests from Ruby. It uses a simple method chaining system for building requests, similar to Python's Requests.

Visualisation of multidimensional data through different Andrews curves: Andrews, D. F. (1972) Plots of High-Dimensional Data. Biometrics, 28(1), 125-136. <doi:10.2307/2528964>.

This package implements a classification method described by Grice (2011, ISBN:978-0-12-385194-9) using binary procrustes rotation; a simplified version of procrustes rotation.

Allows the user to apply nice color gradients to shiny elements. The gradients are extracted from the colorffy website. See <https://www.colorffy.com/gradients/catalog>.

Package for CShapes 2.0, a GIS dataset of country borders (1886-today). Includes functions for data extraction and the computation of distance matrices and -lists.

Templates and data files to support "Discrete Choice Analysis with R", Páez, A. and Boisjoly, G. (2023) <doi:10.1007/978-3-031-20719-8>.

Collects a diverse range of symbolic data and offers a comprehensive set of functions that facilitate the conversion of traditional data into the symbolic data format.

Interactive data exploration with one line of code, automated reporting or use an easy to remember set of tidy functions for low code exploratory data analysis.

Calculates the empirical likelihood ratio and p-value for a mean-type hypothesis (or multiple mean-type hypotheses) based on two samples with possible censored data.

Calculates exact tests and confidence intervals for one-sample binomial and one- or two-sample Poisson cases (see Fay (2010) <doi:10.32614/rj-2010-008>).

This package provides a dataset of favourite numbers, selected from an online poll of over 30,000 people by Alex Bellos (http://pages.bloomsbury.com/favouritenumber).

An implementation in Rcpp / RcppArmadillo of Partial Least Square algorithms. This package includes other functions to perform the double cross-validation and a fast correlation.

Enables users to create simple plots of biological culture plates as well as microplates. Both continuous and discrete values can be plotted onto the plate layout.

This package provides tools to interact nicely with the Genius API <https://docs.genius.com/>. Search hosted content, extract associated metadata and retrieve lyrics with ease.

This package provides a new take on the bar chart. Similar to a waffle style chart but instead of squares the layout resembles a brick wall.

Kernel Machine Score Test for Pathway Analysis in the Presence of Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) <doi: 10.1177/0962280216653427>.

Create maps made of lines. The package contains one function: linemap(). linemap() displays a map made of lines using a raster or gridded data.

This package provides a tool for implementing so called deft approach (see Fisher, David J., et al. (2017) <DOI:10.1136/bmj.j573>) and model visualization.