Simulating synthetic clumped isotope dataset, fitting linear regression models under Bayesian and non-Bayesian frameworks, and generating temperature reconstructions for the same two approaches. Please note that models implemented in this package are described in Roman-Palacios et al. (2021) <doi:10.1002/essoar.10507995.1>.

Statistical summary of STRUCTURE output. STRUCTURE is a K-means clustering method for inferring population structure and assigning individuals to populations using genetic data. Pritchard JK, Stephens M, Donnelly PJ (2000) <DOI:10.1093/genetics/155.2.945>. <https://web.stanford.edu/group/pritchardlab/structure.html>.

This package provides a Bayesian method for Phenome-wide association studies (PheWAS) that identifies causal associations between genetic variants and traits, while simultaneously addressing confounding due to linkage disequilibrium. For details see Manipur et al (2024, Nature Communications) <doi:10.1038/s41467-024-49990-8>.

Create self-contained SVG information cards with embedded Google Fonts', shields-style badges, and custom logos. Cards are fully portable SVG files ideal for dashboards, reports, and web applications. Includes functions to export cards to PNG format and display them in R Markdown and Quarto documents.

Based on random forest principle, DynForest is able to include multiple longitudinal predictors to provide individual predictions. Longitudinal predictors are modeled through the random forest. The methodology is fully described for a survival outcome in: Devaux, Helmer, Genuer & Proust-Lima (2023) <doi: 10.1177/09622802231206477>.

To help you access, transform, analyze, and visualize ForestGEO data, we developed a collection of R packages (<https://forestgeo.github.io/fgeo/>). This package, in particular, helps you to plot ForestGEO data. To learn more about ForestGEO visit <https://forestgeo.si.edu/>.

Interact with Google's Cloud Natural Language API <https://cloud.google.com/natural-language/> (v1) via R. The API has four main features, all of which are available through this R package: syntax analysis and part-of-speech tagging, entity analysis, sentiment analysis, and language identification.

When comparing discrete data mini bubble plots allow displaying more information than traditional bubble plots via colour, shape or labels. Exact overlapping coordinates will be transformed so they surround the original point circularly without overlapping. This is implemented as a position_surround() function for ggplot2'.

This package creates bar plots with rounded corners using ggplot2'. The code in this package was adapted from a solution provided by Stack Overflow user sthoch in the following post <https://stackoverflow.com/questions/62176038/r-ggplot2-bar-chart-with-round-corners-on-top-of-bar>.

Discriminant analysis and data clustering methods for high dimensional data, based on the assumption that high-dimensional data live in different subspaces with low dimensionality proposing a new parametrization of the Gaussian mixture model which combines the ideas of dimension reduction and constraints on the model.

This package provides tools to generate synthetic electronic health records including patients, encounters, vitals, labs, medications, procedures, and allergies, with optional COVID-19-focused and computed tomography (CT)-research views, and export them to comma separated values ('CSV'), SQLite', and Excel formats for researchers and developers.

This package implements the item based collaborative filtering (IBCF) method for continues phenotypes in the context of plant breeding where data are collected for various traits that were studied in various environments proposed by Montesinos-López et al. (2017) <doi:10.1534/g3.117.300309>.

This package provides an easy way to create interactive KPI (key performance indicator) widgets for Quarto dashboards using Crosstalk'. The package enables visualization of key metrics in a structured format, supporting interactive filtering and linking with other Crosstalk'-enabled components. Designed for use in Quarto Dashboards.

Various methods for multivariate outlier detection: arw, a Mahalanobis-type method with an adaptive outlier cutoff value; locout, a method incorporating local neighborhood; pcout, a method for high-dimensional data; mvoutlier.CoDa, a method for compositional data. References are provided in the corresponding help files.

This package provides tools for creating and issuing nicely-formatted text within R diagnostic messages and those messages given during warnings and errors. The formatting of the messages can be customized using templating features. Issues with singular and plural forms can be handled through specialized syntax.

This package provides tools to generate Necklaces, Bracelets, Lyndon words and de Bruijn sequences. The generation relies on integer partitions and uses the KStatistics package. Methods used in the package refers to E. Di Nardo and G. Guarino (2022) <doi:10.48550/arXiv.2208.06855>.

This package provides a comprehensive system for designing and implementing on-farm precision field agronomic trials. You provide field data, tell ofpetrial how to design a trial, and get readily-usable trial design files and a report checks the validity and reliability of the trial design.

Simulating particle movement in 2D space has many application. The particles package implements a particle simulator based on the ideas behind the d3-force JavaScript library. particles implements all forces defined in d3-force as well as others such as vector fields, traps, and attractors.

This package provides functions for estimation and data generation for several piecewise lifetime distributions. The package implements the power piecewise Weibull model, which includes the piecewise Rayleigh and piecewise exponential models as special cases. See Feigl and Zelen (1965) <doi:10.2307/2528247> for methodological details.

This package provides tools to help tag and validate data according to user-specified rules. The safeframe class adds variable level attributes to data.frame columns. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines clearer, more robust, and more reliable.

Create Interactive Graph (Network) Visualizations. shinyCyJS can be used in Shiny apps or viewed from Rstudio Viewer. shinyCyJS includes API to build Graph model like node or edge with customized attributes for R. shinyCyJS is built with cytoscape.js and htmlwidgets R package.

This package provides a framework for performing simulations such as those common in methodological statistics papers. The design principles of this package are described in greater depth in Bien, J. (2016) "The simulator: An Engine to Streamline Simulations," which is available at <arXiv:1607.00021>.

These functions generate data frames on troop deployments and military basing using U.S. Department of Defense data on overseas military deployments. This package provides functions for pulling country-year troop deployment and basing data. Subsequent versions will hopefully include cross-national data on deploying countries.

This package provides functions for density, cumulative density, quantile and simulation of Tukey g-and-h (1977) distributions. The quantile-based transformation (Hoaglin 1985 <doi:10.1002/9781118150702.ch11>) and its reverse transformation, as well as the letter-value based estimates (Hoaglin 1985), are also provided.