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.

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>.

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>).

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.

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.

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.

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.

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.

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.

Fit finite mixture distribution models to grouped data and conditional data by maximum likelihood using a combination of a Newton-type algorithm and the EM algorithm.

Calculate predicted levels and marginal effects, using the delta method to calculate standard errors. This is an R-based version of the margins command from Stata.

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.

Density, distribution function, quantile function and random generation for the 3D Navarro, Frenk & White (NFW) profile. For details see Robotham & Howlett (2018) <arXiv:1805.09550>.

Measure the dependence structure between two random variables with a new correlation coefficient and extend it to hypothesis test, feature screening and false discovery rate control.

Turn tidymodels workflows into objects containing the sufficient sequential equations to perform predictions. These smaller objects allow for low dependency prediction locally or directly in databases.

This package provides a collection of phonetic algorithms including Soundex, Metaphone, NYSIIS, Caverphone, and others. The package is documented in <doi:10.18637/jss.v095.i08>.

Deploy, maintain, and invoke predictive models using the Alteryx Promote REST API. Alteryx Promote is available at the URL: <https://www.alteryx.com/products/alteryx-promote>.

POM-aSPU test evaluates an association between an ordinal response and multiple phenotypes, for details see Kim and Pan (2017) <DOI:10.1002/gepi.22033>.

Utilizing scalable linear algebra packages mainly including BLACS', PBLAS', and ScaLAPACK in double precision via pbdMPI based on ScaLAPACK version 2.0.2.

Estimation of copula using ranks and subsampling. The main feature of this method is that simulation studies show a low sensitivity to dimension, on realistic cases.

Algorithms to compute spherical k-means partitions. Features several methods, including a genetic and a fixed-point algorithm and an interface to the CLUTO vcluster program.