Use health data in the Observational Medical Outcomes Partnership Common Data Model format in Spark'. Functionality includes creating all required tables and fields and creation of a single reference to the data. Native Spark functionality is supported.

This contains functions and data used by the Open Visualization Academy classes on data processing and visualization. The tutorial included with this package requires the gradethis package which can be installed using "remotes::install_github('rstudio/gradethis')".

This package implements the out-of-treatment testing from Kuelpmann and Kuzmics (2020) <doi:10.2139/ssrn.3441675> based on the Vuong Test introduced in Vuong (1989) <doi:10.2307/1912557>. Out-of treatment testing allows for a direct, pairwise likelihood comparison of theories, calibrated with pre-existing data.

This package provides tools to segment fire scars and assess severity and vegetation regeneration using Otsu thresholding on Relative Burn Ratio (RBR) and differenced Normalized Burn Ratio (dNBR) image composites. Includes support for mosaic handling, polygon metrics, post-fire regeneration detection, day-of-year flagging, and validation against reference datasets. Designed for analysis of fire history in the Iberian Peninsula. Input Landsat composites follow the methodology described in Quintero et al. (2025) <doi:10.2139/ssrn.4929831>.

An interface to easily run local language models with Ollama <https://ollama.com> server and API endpoints (see <https://github.com/ollama/ollama/blob/main/docs/api.md> for details). It lets you run open-source large language models locally on your machine.

Import data from Our World in Data', an organisation which publishes research and data on global economic and social issues.

This package provides a layered grammar of graphics that compiles plots to a resolution-independent scene description and renders it through two back-ends: a self-contained SVG writer with embedded JavaScript for interactive figures (tooltips, hover highlighting, zoom, pan and legend toggling) and R's own graphics devices for publication-quality output at any resolution. Geographic layers are first class: a simplified world polygon dataset ships with the package and can be drawn with several map projections, including Robinson, Equal Earth and an orthographic globe. The layered grammar follows Wickham (2010) <doi:10.1198/jcgs.2009.07098>; projections follow Snyder (1987) <doi:10.3133/pp1395> and, for Equal Earth, Savric, Patterson and Jenny (2019) <doi:10.1080/13658816.2018.1504949>; line simplification uses Douglas and Peucker (1973) <doi:10.3138/FM57-6770-U75U-7727>; the default colour scales follow the guidance on perceptually uniform palettes of Crameri, Shephard and Heron (2020) <doi:10.1038/s41467-020-19160-7>.

Computes odds ratios and 95% confidence intervals from a generalized linear model object. It also computes model significance with the chi-squared statistic and p-value and it computes model fit using a contingency table to determine the percent of observations for which the model correctly predicts the value of the outcome. Calculates model sensitivity and specificity.

Create regression tables for publication. Currently supports lm', glm', survreg', and ivreg outputs.

This package provides native access to the Open Neural Network Exchange (ONNX) Runtime <https://onnxruntime.ai/>, which is a performant engine for running machine learning models that are saved to a standardized format. Rather than interfacing with ONNX via Python', as in the official onnx package, onnxr directly interfaces with the runtime's C++ API via cpp11'. Models saved to .onnx files can be loaded and run on various backends, including CPUs and Apple's CoreML library.

This package provides a generalised data structure for fast and efficient loading and data munching of sparse omics data. The OmicFlow requires an up-front validated metadata template from the user, which serves as a guide to connect all the pieces together by aligning them into a single object that is defined as an omics class. Once this unified structure is established, users can perform manual subsetting, visualisation, and statistical analysis, or leverage the automated autoFlow method to generate a comprehensive report.

Search and extract data from the Organization for Economic Cooperation and Development (OECD).

Help and demo in Spanish of the orloca package. Ayuda y demo en espanol del paquete orloca. Objetos y metodos para manejar y resolver el problema de localizacion de suma minima, tambien conocido como problema de Fermat-Weber. El problema de localizacion de suma minima busca un punto tal que la suma ponderada de las distancias a los puntos de demanda se minimice. Vease "The Fermat-Weber location problem revisited" por Brimberg, Mathematical Programming, 1, pag. 71-76, 1995. <DOI: 10.1007/BF01592245>. Se usan algoritmos generales de optimizacion global para resolver el problema, junto con el metodo especifico Weiszfeld, vease "Sur le point pour lequel la Somme des distance de n points donnes est minimum", por Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pag. 355-386, 1937 o "On the point for which the sum of the distances to n given points is minimum", por E. Weiszfeld y F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.

This package provides tools for annotating characters (character matrices) with anatomical and phenotype ontologies. Includes functions for visualising character annotations and creating simple queries using ontological relationships.

An interface to the Apache OpenNLP tools (version 1.5.3). The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text written in Java. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. See <https://opennlp.apache.org/> for more information.

Compound deconvolution for chromatographic data, including gas chromatography - mass spectrometry (GC-MS) and comprehensive gas chromatography - mass spectrometry (GCxGC-MS). The package includes functions to perform independent component analysis - orthogonal signal deconvolution (ICA-OSD), independent component regression (ICR), multivariate curve resolution (MCR-ALS) and orthogonal signal deconvolution (OSD) alone.

Various tools developed as part of the Open-CESP (Centre de recherche en Epidémiologie et Santé des Populations) initiative to generate and evaluate synthetic datasets for statistical disclosure control. This includes tools to investigate the risk-utility tradeoff achievable with given synthesis methods, as well as statistical tools to estimate (conditional) probability distributions. The main eventual aim is to help researchers and statisticians disseminate open research data.

Combine the air quality data analysis methods of openair with the JavaScript Leaflet (<https://leafletjs.com/>) library. Functionality includes plotting site maps, "directional analysis" figures such as polar plots, and air mass trajectories.

This package provides a growing collection of personal utility functions. Currently provides tools to parse Rich Text Format (RTF) files and extract their tables into data frames, automatically detecting header rows, merging multi-page tables, and resolving merged cells. Particularly useful for tables produced by SAS or by the r2rtf package, which are commonly used for clinical trial and regulatory reporting.

Estimation of value and hedging strategy of call and put options, based on optimal hedging and Monte Carlo method, from Chapter 3 of Statistical Methods for Financial Engineering', by Bruno Remillard, CRC Press, (2013).

This package provides unified workflows for quality control, normalization, and visualization of proteomic and metabolomic data. The package simplifies preprocessing through automated imputation, scaling, and principal component analysis (PCA)-based exploratory analysis, enabling researchers to prepare omics datasets efficiently for downstream statistical and machine learning analyses.

Calculating the stability of random forest with certain numbers of trees. The non-linear relationship between stability and numbers of trees is described using a logistic regression model and used to estimate the optimal number of trees.

This package provides functions for plotting Australia's coastline and state boundaries.

Supplemental functions and data for OpenIntro resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.