This package contains utilities and functions for the cleaning, processing and management of patient level public health data for surveillance and analysis held by the UK Health Security Agency, UKHSA.

FastGit <https://doc.fastgit.org/> works like a mirror of GitHub to make significant acceleration. fgitR is a package to do git operation with FastGit automatically.

Collection of utility functions used in the KEHRA project (see http://www.brunel.ac.uk/ife/britishcouncil). It refers to the multidimensional analysis of air pollution, weather and health data.

An efficient procedure for feature selection for generalized linear models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian regression. Adaptive ridge algorithms are used to fit the models.

An interface to LuaJIT <https://luajit.org>, a just-in-time compiler for the Lua scripting language <https://www.lua.org>. Allows users to run Lua code from R'.

This package implements a high dimensional mediation analysis algorithm using Local False Discovery Rates. The methodology is described in Roy and Zhang (2024) <doi:10.48550/arXiv.2402.13933>.

This package provides a rmarkdown template that supports company logo, contact info, watermarks and more. Currently restricted to Latex'/'Markdown'; a similar HTML theme will be added in the future.

This package provides a set of convenience functions as well as geographical/political data about Nigeria, aimed at simplifying work with data and information that are specific to the country.

It provides the density and random number generator for the Scale-Shape Mixtures of Skew-Normal Distributions proposed by Jamalizadeh and Lin (2016) <doi:10.1007/s00180-016-0691-1>.

Take real or simulated data and salt it with errors commonly found in the wild, such as pseudo-OCR errors, Unicode problems, numeric fields with nonsensical punctuation, bad dates, etc.

An implementation of statistical tools for the analysis of rotation-valued time series and functional data. It relies on pre-existing quaternion data structure provided by the Eigen C++ library.

The variable importance is calculated using knock off variables. Then output can be provided in numerical and graphical form. Meredith L Wallace (2023) <doi:10.1186/s12874-023-01965-x>.

This package provides a collection of methods for the robust analysis of univariate and multivariate functional data, possibly in high-dimensional cases, and hence with attention to computational efficiency and simplicity of use. See the R Journal publication of Ieva et al. (2019) <doi:10.32614/RJ-2019-032> for an in-depth presentation of the roahd package. See Aleman-Gomez et al. (2021) <arXiv:2103.08874> for details about the concept of depthgram.

This package provides tools for qPCR data analysis using Delta Ct and Delta Delta Ct methods, including t-tests, ANOVA, ANCOVA, repeated-measures models, and publication-ready visualizations. The package supports multiple target, and multiple reference genes, and uses a calculation framework adopted from Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods.

This package provides a parallel function for multivariate outlier detection named modified Stahel-Donoho estimators is contained in this package. The function RMSDp() is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. This function is for higher dimensional datasets that cannot be handled by a single core function RMSD() included in RMSD package. See Wada and Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> for the detail of the algorithm.

This package provides a programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/developer/summary>). GBIF is a database of species occurrence records from sources all over the globe. rgbif includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the GBIF tile map service to make rasters summarizing huge amounts of data.

This package provides functionality to define and train neural networks similar to PyTorch but written entirely in R using the libtorch library. It also supports low-level tensor operations and GPU acceleration.

This package provides a unified R graphics backend. Render R graphics fast and easy to many common file formats. It provides a thread safe C interface for asynchronous rendering of R graphics.

This package provides an implementation of many measures for the assessment of the stability of feature selection. Both simple measures and measures which take into account the similarities between features are available.

Methodology for supervised clustering of potentially many predictor variables, such as genes etc., in time series datasets Provides functions that help the user assigning genes to predefined set of model profiles.

Cluster genes to functional groups with E-M process. Iteratively perform TF assigning and Gene assigning, until the assignment of genes did not change, or max number of iterations is reached.

The package implements two main algorithms to answer two key questions: a SCORE (Stable Clustering at Optimal REsolution) to find subpopulations, followed by scGPS to investigate the relationships between subpopulations.

Analysis of moderation (ANOMO) method conceptualizes the difference and equivalence tests as a moderation problem to test the difference and equivalence of two estimates (e.g., two means or two effects).

This package provides tools to read, write, parse, and analyze forest fire history data (e.g. FHX). Described in Malevich et al. (2018) <doi:10.1016/j.dendro.2018.02.005>.