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 a function built on ggplot2 that visualizes pairwise BLAST alignment results as chord diagrams, intuitively displaying homologous regions between query and subject sequences.

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.

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.

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.

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.

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>.

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.

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>.

This package provides simple methods to extract data portions from various objects. The relative portion size and the way the portion is selected can be chosen.

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

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>.

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>.

This package provides functions to extract citation data from Google Scholar. Convenience functions are also provided for comparing multiple scholars and predicting future h-index values.

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.

This package provides a suite of functions for visualising ternary probabilistic forecasts, as discussed in the paper by Jupp (2012) <doi:10.1098/rsta.2011.0350>.

Create interactive tables, calendars, charts and markdown WYSIWYG editor with TOAST UI <https://ui.toast.com/> libraries to integrate in shiny applications or rmarkdown HTML documents.

With the objective of including data from RSS feeds into your analysis, tidyRSS parses RSS, Atom and JSON feeds and returns a tidy data frame.

This package provides a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger compliant API.

This package provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation):

• Ratcliff diffusion model (Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) based on C code by Andreas and Jochen Voss and

• linear ballistic accumulator (LBA; Brown & Heathcote, 2008, <doi:10.1016/j.cogpsych.2007.12.002>) with different distributions underlying the drift rate.

Rare variant association tests: burden tests (Bocher et al. 2019 <doi:10.1002/gepi.22210>) and the Sequence Kernel Association Test (Bocher et al. 2021 <doi:10.1038/s41431-020-00792-8>) in the whole genome using the RAVA-FIRST approach (Bocher et al. 2022 <doi:10.1371/journal.pgen.1009923>). Ravages also enables to perform genetic simulations (Bocher et al. 2023 <doi:10.1002/gepi.22529>).