Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.

Semissupervised model for geographical document classification (Watanabe 2018) <doi:10.1080/21670811.2017.1293487>. This package currently contains seed dictionaries in English, German, French, Spanish, Italian, Russian, Hebrew, Arabic, Turkish, Japanese and Chinese (Simplified and Traditional).

Estimating the number of essential genes in a genome on the basis of data from a random transposon mutagenesis experiment, through the use of a Gibbs sampler. Lamichhane et al. (2003) <doi:10.1073/pnas.1231432100>.

Supports the modeling of ordinal random variables, like the outcomes of races, via Softmax regression, under the Harville <doi:10.1080/01621459.1973.10482425> and Henery <doi:10.1111/j.2517-6161.1981.tb01153.x> models.

This package provides a system for calculating the minimum total sample size needed to achieve a prespecified power or the optimal allocation for each treatment group with a fixed total sample size to maximize the power.

Facilitates analysis of paleontological sequences of trait values. Functions are provided to fit, using maximum likelihood, simple evolutionary models (including unbiased random walks, directional evolution,stasis, Ornstein-Uhlenbeck, covariate-tracking) and complex models (punctuation, mode shifts).

Simulate dose regimens for pharmacokinetic-pharmacodynamic (PK-PD) models described by differential equation (DE) systems. Simulation using ADVAN-style analytical equations is also supported (Abuhelwa et al. (2015) <doi:10.1016/j.vascn.2015.03.004>).

This package provides a shiny app that allows to access and use the INVEKOS API for field polygons in Austria. API documentation is available at <https://gis.lfrz.gv.at/api/geodata/i009501/ogc/features/v1/>.

This package provides a set of tools to implement the non-parametric bounds and Bayesian methods for assessing post-treatment bias developed in Blackwell, Brown, Hill, Imai, and Yamamoto (2025) <doi:10.1017/pan.2025.3>.

Training and validation of a custom (or data-driven) Structural Equation Models using Deep Neural Networks or Machine Learning algorithms, which extend the fitting procedures of the SEMgraph R package <doi:10.32614/CRAN.package.SEMgraph>.

This package provides a collection of recycled and modified R functions to aid in file manipulation, data exploration, wrangling, optimization, and object manipulation. Other functions aid in convenient data visualization, loop progression, software packaging, and installation.

Secure handling of API keys can be difficult. This package provides secure convenience functions for entering / handling API keys and opening connections via inversion of control on those keys. Works seamlessly between production and developer environments.

Instance feature calculation and evolutionary instance generation for the traveling salesman problem. Also contains code to "morph" two TSP instances into each other. And the possibility to conveniently run a couple of solvers on TSP instances.

The goal of this package will be to provide a simple interface for automatic machine learning that fits the tidymodels framework. The intention is to work for regression and classification problems with a simple verb framework.

Multi-caller variant analysis pipeline for targeted analysis sequencing (TAS) data. Features a modular, automated workflow that can start with raw reads and produces a user-friendly PDF summary and a spreadsheet containing consensus variant information.

This package provides an htmlwidgets interface to VChart.js'. VChart', more than just a cross-platform charting library, but also an expressive data storyteller. VChart examples and documentation are available here: <https://www.visactor.io/vchart>.

This package provides routing based on the path-tree Rust crate. The routing is general purpose in the sense that any type of R object can be associated with a path, not just a handler function.

This package provides functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities (I. Fellegi & A. Sunter (1969) <doi:10.1080/01621459.1969.10501049>, T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007), "Data Quality and Record Linkage Techniques", ISBN:978-0-387-69502-0), forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage. Focus is on memory, CPU performance and flexibility.

Analyzes revisions in real-time time series vintages. The package converts between wide revision triangles and tidy long vintages, extracts selected releases, computes revision series, visualizes vintage paths, and summarizes revision properties such as bias, dispersion, autocorrelation, and news-noise diagnostics. It also identifies efficient releases and estimates state-space models for revision nowcasting. Methods are based on Howrey (1978) <doi:10.2307/1924972>, Jacobs and Van Norden (2011) <doi:10.1016/j.jeconom.2010.04.010>, and Kishor and Koenig (2012) <doi:10.1198/jbes.2010.08169>.

This package provides a portable Shiny tool to explore patient-level electronic health record data and perform chart review in a single integrated framework. This tool supports browsing clinical data in many different formats including multiple versions of the OMOP common data model as well as the MIMIC-III data model. In addition, chart review information is captured and stored securely via the Shiny interface in a REDCap (Research Electronic Data Capture) project using the REDCap API. See the ReviewR website for additional information, documentation, and examples.

RTG Tools is a subset of RTG Core that includes several useful utilities for dealing with VCF files and sequence data. Probably the most interesting is the vcfeval command which performs sophisticated comparison of VCF files.

This is a legacy project, do not use it for new projects. Ruby 2.3 and later should make this obsolete. kgio provides non-blocking I/O methods for Ruby without raising exceptions on EAGAIN and EINPROGRESS.

Rasterize only specific layers of a ggplot2 plot while simultaneously keeping all labels and text in vector format. This allows users to keep plots within the reasonable size limit without losing vector properties of the scale-sensitive information.

This package provides helpers for reordering factor levels (including moving specified levels to front, ordering by first appearance, reversing, and randomly shuffling), and tools for modifying factor levels (including collapsing rare levels into other, "anonymizing", and manually "recoding").