Perform the analysis of the World Health Organization (WHO) Pharmacovigilance database VigiBase (Extract Case Level version), <https://who-umc.org/> e.g., load data, perform data management, disproportionality analysis, and descriptive statistics. Intended for pharmacovigilance routine use or studies. This package is NOT supported nor reflect the opinion of the WHO, or the Uppsala Monitoring Centre. Disproportionality methods are described by Norén et al (2013) <doi:10.1177/0962280211403604>.

An advanced, interactive data table and data explorer for R, delivered as a modern, self-contained htmlwidget with a high-performance virtualized grid. ViewR renders Kaggle'-style micro-dashboard column headers complete with data-type badges, mini distribution spark-histograms, and data-completeness (missingness) bars. It provides hover metadata cards, a sliding Data Insights drawer with interactive histograms and Pareto category charts, a multi-condition visual query builder (AND/OR), a column visibility picker, and a reproducible code generator that emits dplyr', base R, and SQL that matches the active filter and column state. The interface is implemented entirely in dependency-free vanilla JavaScript (no React or build toolchain) and works in the RStudio'/'Positron Viewer, inside Shiny apps, in R Markdown'/'Quarto', or as a portable standalone HTML file. A single call to viewr() opens the explorer; the legacy Shiny'-gadget ViewR() editor remains available.

Uses large language models to create poems about R packages. Currently contains the roses() function to make "roses are red, ..." style poems and the prompt() function to only assemble the prompt without submitting it to the model.

Computation of volatility impulse response function for multivariate time series model using algorithm by Jin, Lin and Tamvakis (2012) <doi:10.1016/j.eneco.2012.03.003>.

Generate Venn diagrams from two or three sets, displaying the overlapping items as lists in the appropriate sections. The lists can be split into columns or shortened for large sets and the plot is generated using ggplot2 allowing further customisations.

Constructs a virtual population from fertility and mortality rates for any country, calendar year and birth cohort in the Human Mortality Database <https://www.mortality.org> and the Human Fertility Database <https://www.humanfertility.org>. Fertility histories are simulated for every individual and their offspring, producing a multi-generation virtual population.

This package provides functions for estimation (parametric, semi-parametric and non-parametric) of copula-based dependence coefficients between a finite collection of random vectors, including phi-dependence measures and Bures-Wasserstein dependence measures. An algorithm for agglomerative hierarchical variable clustering is also implemented. Following the articles De Keyser & Gijbels (2024) <doi:10.1016/j.jmva.2024.105336>, De Keyser & Gijbels (2024) <doi:10.1016/j.ijar.2023.109090>, and De Keyser & Gijbels (2024) <doi:10.48550/arXiv.2404.07141>.

Via Foundry API provides streamlined tools for interacting with and extracting data from structured responses, particularly for use cases involving hierarchical data from Foundry's API. It includes functions to fetch and parse process-level and file-level metadata, allowing users to efficiently query and manipulate nested data structures. Key features include the ability to list all unique process names, retrieve file metadata for specific or all processes, and dynamically load or download files based on their type. With built-in support for handling various file formats (e.g., tabular and non-tabular files) and seamless integration with API through authentication, this package is designed to enhance workflows involving large-scale data management and analysis. Robust error handling and flexible configuration ensure reliable performance across diverse data environments. Please consult the documentation for the API endpoint for your installation.

Collects tweets and metadata for threaded conversations and generates networks.

Analysing vital statistics based on tools consistent with the tidyverse. Tools are provided for data visualization, life table calculations, computing net migration numbers, Lee-Carter modelling; functional data modelling and forecasting.

This package provides tools for estimating vaccine effectiveness and related metrics. The vaccineff_data class manages key features for preparing, visualizing, and organizing cohort data, as well as estimating vaccine effectiveness. The results and model performance are assessed using the vaccineff class.

Generates interactive plots for analysing and visualising three-class high dimensional data. It is particularly suited to visualising differences in continuous attributes such as gene/protein/biomarker expression levels between three groups. Differential gene/biomarker expression analysis between two classes is typically shown as a volcano plot. However, with three groups this type of visualisation is particularly difficult to interpret. This package generates 3D volcano plots and 3-way polar plots for easier interpretation of three-class data.

Traces information spread through interactions between features, utilising information theory measures and a higher-order generalisation of the concept of widest paths in graphs. In particular, vistla can be used to better understand the results of high-throughput biomedical experiments, by organising the effects of the investigated intervention in a tree-like hierarchy from direct to indirect ones, following the plausible information relay circuits. Due to its higher-order nature, vistla can handle multi-modality and assign multiple roles to a single feature.

In order to make it easy to use variance reduction algorithms for any simulation, this framework can help you. We propose user friendly and easy to extend framework. Antithetic Variates, Inner Control Variates, Outer Control Variates and Importance Sampling algorithms are available in the framework. User can write its own simulation function and use the Variance Reduction techniques in this package to obtain more efficient simulations. An implementation of Asian Option simulation is already available within the package. See Kemal Dinçer Dingeç & Wolfgang Hörmann (2012) <doi:10.1016/j.ejor.2012.03.046>.

This package provides two functions frameableWidget()', and frameWidget()'. The frameableWidget() is used to add extra code to a htmlwidget which allows is to be rendered correctly inside a responsive iframe'. The frameWidget() is a htmlwidget which displays content of another htmlwidget inside a responsive iframe'. These functions allow for easier embedding of htmlwidgets in content management systems such as wordpress', blogger etc. They also allow for separation of widget content from main HTML content where CSS of the main HTML could interfere with the widget.

This package provides a toolkit to set up an R data package in a consistent structure. Automates tasks like tidy data export, data dictionary documentation, README and website creation, and citation management.

Graphical data analysis of accelerated life tests. Methods derived from Wayne Nelson (1990, ISBN: 9780471522775), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6).

This package provides insight into how the best hand for a poker game changes based on the game dealt, players who stay in until the showdown and wildcards added to the base game. At this time the package does not support player tactics, so draw poker variants are not included.

This package provides API access to the Walmart Open API <https://developer.walmartlabs.com/>, that contains data about stores, Value of the day and products which includes names, sale prices, shipping rates and taxonomies.

Estimates the standard and weighted Elo (WElo, Angelini et al., 2022 <doi:10.1016/j.ejor.2021.04.011>) rates. The current version provides Elo and WElo rates for tennis, according to different systems of weights (games or sets) and scale factors (constant, proportional to the number of matches, with more weight on Grand Slam matches or matches played on a specific surface). Moreover, the package gives the possibility of estimating the (bootstrap) standard errors for the rates. Finally, the package includes betting functions that automatically select the matches on which place a bet.

Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including FBref', transfer and valuations data from Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from Understat'<https://understat.com/> and fotmob'<https://www.fotmob.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.

Computes exact observation weights for the Kalman filter and smoother, following Koopman and Harvey (2003) <www.sciencedirect.com/science/article/pii/S0165188902000611>. The package provides tools for analyzing linear Gaussian state-space models, allowing users to quantify the contribution of individual observations to filtered and smoothed state estimates. These weights can be used for interpretation, decomposition, and diagnostic analysis in time series models, including applications such as dynamic factor models. See the README for examples.

Set of functions that improves the graphical presentations of the functions: wave.correlation and spin.correlation (waveslim package, Whitcher 2012) and the wave.multiple.correlation and wave.multiple.cross.correlation (wavemulcor package, Fernandez-Macho 2012b). The plot outputs (heatmaps) can be displayed in the screen or can be saved as PNG or JPG images or as PDF or EPS formats. The W2CWM2C package also helps to handle the (input data) multivariate time series easily as a list of N elements (times series) and provides a multivariate data set (dataexample) to exemplify its use. A description of the package was published in a scientific paper: Polanco-Martinez and Fernandez-Macho (2014), <doi:10.1109/MCSE.2014.96>.

Shows the relationship between an independent and dependent variable through Weight of Evidence and Information Value.