This package performs score test using saddlepoint approximation to estimate the null distribution. It also prepares summary statistics for meta-analysis and performs meta-analysis to combine multiple association results.

This package provides auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).

16S rRNA gene sequencing data to study changes in the faecal microbiota of 12 volunteers during a human challenge study with ETEC (H10407) and subsequent treatment with ciprofloxacin.

Identification of interactions between binary variables using Logic Regression. Can, e.g., be used to find interesting SNP interactions. Contains also a bagging version of logic regression for classification.

Grafts the extinct bird species from the Avotrex database (Sayol et al., in review) on to the BirdTree phylogenies <https://birdtree.org>, using a set of different commands.

Anytime-valid sequential estimation of the p-value of a test calibrated by Monte-Carlo simulation, as described in Stoepker & Castro (2024) <doi:10.48550/arXiv.2409.18908>.

Domain mean estimation with monotonicity or block monotone constraints. See Xu X, Meyer MC and Opsomer JD (2021)<doi:10.1016/j.jspi.2021.02.004> for more details.

R interface for RAPIDS cuML (<https://github.com/rapidsai/cuml>), a suite of GPU-accelerated machine learning libraries powered by CUDA (<https://en.wikipedia.org/wiki/CUDA>).

This package contains the basic functions to apply the unified framework for partitioning the drivers of stability of ecological communities. Segrestin et al. (2024) <doi:10.1111/geb.13828>.

Systematically Run R checks against multiple packages. Checks are run in parallel with strategies to minimize dependency installation. Provides out of the box interface for running reverse dependency check.

This package provides a domain-specific language for specifying translating recursions into dynamic-programming algorithms. See <https://en.wikipedia.org/wiki/Dynamic_programming> for a description of dynamic programming.

Non-iterative estimator for the cumulative distribution of a doubly truncated variable. de Uña-à lvarez J. (2018) <doi:10.1007/978-3-319-73848-2_37>.

Second and backward-incompatible version of R package eodhd <https://eodhd.com/>, extended with a cache and quota system, also offering functions for cleaning and aggregating the financial data.

The FastPCS algorithm of Vakili and Schmitt (2014) <doi:10.1016/j.csda.2013.07.021> for robust estimation of multivariate location and scatter and multivariate outliers detection.

This package provides methods to solve Fuzzy Linear Programming Problems with fuzzy constraints (following different approaches proposed by Verdegay, Zimmermann, Werners and Tanaka), fuzzy costs, and fuzzy technological matrix.

This is a GitHub API wrapper for R. <https://docs.github.com/en/rest> It uses the gh package but has things wrapped up for convenient use cases.

This package provides a tool which allows users the ability to intuitively create flexible, reproducible portable document format reports comprised of aesthetically pleasing tables, images, plots and/or text.

Fast algorithms for robust estimation with large samples of multivariate observations. Estimation of the geometric median, robust k-Gmedian clustering, and robust PCA based on the Gmedian covariation matrix.

Retrieve datasets from the Global Data Lab website <https://globaldatalab.org> directly into R data frames. Functions are provided to reference available options (indicators, levels, countries, regions) as well.

This package provides a simple implementation of doughnut plots - pie charts with a blank center. The package is named after Homer Simpson - arguably the best-known lover of doughnuts.

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>.

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).