Flexible and efficient cleaning of data with interactivity. datacleanr facilitates best practices in data analyses and reproducibility with built-in features and by translating interactive/manual operations to code. The package is designed for interoperability, and so seamlessly fits into reproducible analyses pipelines in R'.

This package provides a disk-based data manipulation tool for working with large-than-RAM datasets. Aims to lower the barrier-to-entry for manipulating large datasets by adhering closely to popular and familiar data manipulation paradigms like dplyr verbs and data.table syntax.

The goal of forstringr is to enable complex string manipulation in R especially to those more familiar with LEFT(), RIGHT(), and MID() functions in Microsoft Excel. The package combines the power of stringr with other manipulation packages such as dplyr and tidyr'.

Graph clustering using an agglomerative algorithm to maximize the integrated classification likelihood criterion and a mixture of stochastic block models. The method is described in the article "Model-based clustering of multiple networks with a hierarchical algorithm" by T. Rebafka (2022) <arXiv:2211.02314>.

This package provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class incidence2 is used to store computed incidence and can be easily manipulated, subsetted, and plotted.

This is an extension package to logrx', which is a log creation program focused on Clinical Reporting within the Pharma Industry. This package enables a simple shiny-based Add-in that provides a point and click interface to produce a log for a single program.

This package provides a collection of moment-matching methods for computing the cumulative distribution function of a positively-weighted sum of chi-squared random variables. Methods include the Satterthwaite-Welch method, Hall-Buckley-Eagleson method, Wood's F method, and the Lindsay-Pilla-Basak method.

Regression methods for the meta-SDT model. The package implements methods for cognitive experiments of metacognition as described in Kristensen, S. B., Sandberg, K., & Bibby, B. M. (2020). Regression methods for metacognitive sensitivity. Journal of Mathematical Psychology, 94. <doi:10.1016/j.jmp.2019.102297>.

In this implementation of the Naive Bayes classifier following class conditional distributions are available: Bernoulli', Categorical', Gaussian', Poisson', Multinomial and non-parametric representation of the class conditional density estimated via Kernel Density Estimation. Implemented classifiers handle missing data and can take advantage of sparse data.

This package performs minimax linkage hierarchical clustering. Every cluster has an associated prototype element that represents that cluster as described in Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering with Prototypes via Minimax Linkage," The Journal of the American Statistical Association, 106(495), 1075-1084.

Implementation of PsychroLib <https://github.com/psychrometrics/psychrolib> library which contains functions to enable the calculation properties of moist and dry air in both metric (SI) and imperial (IP) systems of units. References: Meyer, D. and Thevenard, D (2019) <doi:10.21105/joss.01137>.

This package provides a pipeline to perform small area estimation and prevalence mapping of binary indicators using health and demographic survey data, described in Fuglstad et al. (2022) <doi:10.48550/arXiv.2110.09576> and Wakefield et al. (2020) <doi:10.1111/insr.12400>.

Input/Output, processing and visualization of spectra taken with different spectrometers, including SVC (Spectra Vista), ASD and PSR (Spectral Evolution). Implements an S3 class spectra that other packages can build on. Provides methods to access, plot, manipulate, splice sensor overlap, vector normalize and smooth spectra.

This package provides an intuitive interface for working with the competing risk endpoints. The package wraps the cmprsk package, and exports functions for univariate cumulative incidence estimates and competing risk regression. Methods follow those introduced in Fine and Gray (1999) <doi:10.1002/sim.7501>.

Converts XML documents to R dataframes and dataframes to XML documents. A wide variety of options allows for different XML formats and flexible control of the conversion process. Results can be exported to CSV and Excel, if desired. Also converts XML data to R lists.

The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

This package provides utilities to understand and describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion such as Highest Density Interval (HDI), and indices used for null-hypothesis testing (such as ROPE percentage and pd).

Rachana is a Malayalam font designed by Hussain K H. The project was part of Rachana Aksharavedi for the original script of Malayalam in computing. Rachana has about 1,200+ glyphs for Malayalam and contains glyphs required for printing old Malayalam books without compromising the writing style.

cl-rmath is a simple, autogenerated foreign interface for the standalone R API libRmath. There has been no effort to provide a high-level interface for the original library, instead, this library is meant to serve as a building block for such an interface.

Example data for MEDIPS and QSEA packages, consisting of chromosome 22 MeDIP and control/Input sample data. Additionally, the package contains MeDIP seq data from 3 NSCLC samples and adjacent normal tissue (chr 20-22). All data has been aligned to human genome hg19.

ShinyÉPICo is a graphical pipeline to analyze Illumina DNA methylation arrays (450k or EPIC). It allows to calculate differentially methylated positions and differentially methylated regions in a user-friendly interface. Moreover, it includes several options to export the results and obtain files to perform downstream analysis.

This package provides a modeling package compiling applicability domain methods in R. It combines different methods to measure the amount of extrapolation new samples can have from the training set. See Gadaleta et al (2016) <doi:10.4018/IJQSPR.2016010102> for an overview of applicability domains.

Implementation of the bootkmeans algorithm, a bootstrap augmented k-means algorithm that returns probabilistic cluster assignments. From paper by Ghashti, J.S., Andrews, J.L. Thompson, J.R.J., Epp, J. and H.S. Kochar (2025), "A bootstrap augmented k-means algorithm for fuzzy partitions" (Submitted).

Efficient object-oriented R6 dictionary capable of holding objects of any class, including R6. Typed and untyped dictionaries are provided as well as the usual dictionary methods that are available in other OOP languages, for example listing keys, items, values, and methods to get/set these.