Allows the simulation of the recruitment and both the event and treatment phase of a clinical trial. Based on these simulations, the timing of interim analyses can be assessed.

This package provides a novel implementation that solves the linear distance weighted discrimination and the kernel distance weighted discrimination. Reference: Wang and Zou (2018) <doi:10.1111/rssb.12244>.

This package provides a disciplined, lazy subset of dplyr semantics for MongoDB aggregation pipelines. Queries remain lazy until collect() and compile into MongoDB-native aggregation stages.

Create interactive analytic networks. It joins the data analysis power of R to obtain coincidences, co-occurrences and correlations, and the visualization libraries of JavaScript in one package.

Data sets for network analysis related to People Analytics. Contains various data sets from the book Handbook of Graphs and Networks in People Analytics by Keith McNulty (2021).

This package provides functions for phenological data preprocessing, modelling and result handling. For more information, please refer to Lange et al. (2016) <doi:10.1007/s00484-016-1161-8>.

This package provides a novel tool for generating a piecewise constant estimation list of increasingly complex predictors based on an intensive and comprehensive search over the entire covariate space.

This package implements the s-values proposed by Ed. Leamer. It provides a context-minimal approach for sensitivity analysis using extreme bounds to assess the sturdiness of regression coefficients.

Multi-generational pedigree inference from incomplete data on hundreds of SNPs, including parentage assignment and sibship clustering. See Huisman (2017) (<DOI:10.1111/1755-0998.12665>) for more information.

Simple utilities to generate a Dockerfile from a directory or project, build the corresponding Docker image, push the image to DockerHub, and publicly share the project via Binder.

Historical voting data of the United Nations General Assembly. This includes votes for each country in each roll call, as well as descriptions and topic classifications for each vote.

This package provides functions to fit Gaussian linear model by maximising the residual log likelihood where the covariance structure can be written as a linear combination of known matrices. It can be used for multivariate models and random effects models. It aims to provide an easy straight forward manner to specify random effects models, including random interactions. The code is optimized to use Sherman Morrison Woodbury identities for matrix inversion in random effects models.

This package provides a collection of functions for computing "r-values" from various kinds of user input such as MCMC output or a list of effect size estimates and associated standard errors. Given a large collection of measurement units, the r-value, r, of a particular unit is a reported percentile that may be interpreted as the smallest percentile at which the unit should be placed in the top r-fraction of units.

Haplotype simulations of rare variant genetic data that emulates real data can be performed with RAREsim. RAREsim uses the expected number of variants in MAC bins - either as provided by default parameters or estimated from target data - and an abundance of rare variants as simulated HAPGEN2 to probabilistically prune variants. RAREsim produces haplotypes that emulate real sequencing data with respect to the total number of variants, allele frequency spectrum, haplotype structure, and variant annotation.

This package provides a function to infer pathway activity from gene expression. It contains the linear model inferred in the publication "Perturbation-response genes reveal signaling footprints in cancer gene expression".

This package provides a collection of reference expression datasets with curated cell type labels, for use in procedures like automated annotation of single-cell data or deconvolution of bulk RNA-seq.

This package provides some helpful extensions and modifications to the ggplot2 package to combine multiple ggplot2 plots into one and label them with letters, as is often required for scientific publications.

This package provides a generalized estimating equations solver for parameters in mean, scale, and correlation structures, through mean link, scale link, and correlation link. It can also handle clustered categorical responses.

This package provides functions for regulation, decomposition and analysis of space-time series. The pastecs library is a PNEC-Art4 and IFREMER initiative to bring PASSTEC 2000 functionalities to R.

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

The ROCTracer library provides APIs for tracing (also asynchronous) runtime calls in an application. It is intended for tracing ROCm API calls in GPU applications, such as kernel dispatches and memory moves.

CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.

This package is for analysis of SILAC labeled complexome profiling data. It uses peptide table in tab-delimited format as an input and produces ready-to-use tables and plots.

This package provides a general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments.