This package provides R access to election results data. Wraps elex (https://github.com/newsdev/elex/), a Python package and command line tool for fetching and parsing Associated Press election results.

The interface package to access data from the EpiGraphDB <https://epigraphdb.org> platform. It provides easy access to the EpiGraphDB platform with functions that query the corresponding REST endpoints on the API <https://api.epigraphdb.org> and return the response data in the tibble data frame format.

Expert Algorithm Verbal Autopsy assigns causes of death to 2016 WHO Verbal Autopsy Questionnaire data. odk2EAVA() converts data to a standard input format for cause of death determination building on the work of Thomas (2021) <https://cran.r-project.org/src/contrib/Archive/CrossVA/>. codEAVA() uses the presence and absence of signs and symptoms reported in the Verbal Autopsy interview to diagnose common causes of death. A deterministic algorithm assigns a single cause of death to each Verbal Autopsy interview record using a hierarchy of all common causes for neonates or children 1 to 59 months of age.

An assistant built on large language models that helps interpret statistical model outputs in R by generating concise, audience-specific explanations.

Facilitates basic spatial edge correction to point pattern data.

Forecasting time series with different decomposition based ARIMA models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>.

This package provides an interface to the European Central Bank's Data Portal API, allowing for programmatic retrieval of a vast quantity of statistical data.

Support functions for R-based "EQUALCompareImages - Compare similarity between and within images" shiny application which allow researchers without coding skills or expertise in image comparison algorithms to compare images. Gurusamy,K (2025)<doi:10.5281/zenodo.16994047>.

Interactive labelling of scatter plots, volcano plots and Manhattan plots using a shiny and plotly interface. Users can hover over points to see where specific points are located and click points on/off to easily label them. Labels can be dragged around the plot to place them optimally. Plots can be exported directly to PDF for publication. For plots with large numbers of points, points can optionally be rasterized as a bitmap, while all other elements (axes, text, labels & lines) are preserved as vector objects. This can dramatically reduce file size for plots with millions of points such as Manhattan plots, and is ideal for publication.

This package provides functions for the Bayesian analysis of extreme value models, using Markov chain Monte Carlo methods. Allows the construction of both uninformative and informed prior distributions for common statistical models applied to extreme event data, including the generalized extreme value distribution.

This package provides utility functions for standardizing economic entity (economy, aggregate, institution, etc.) name and id in economic datasets such as those published by the International Monetary Fund and World Bank. Aims to facilitate consistent data analysis, reporting, and joining across datasets. Used as a foundational building block in the EconDataverse family of packages (<https://www.econdataverse.org>).

This package provides classes and helper functions for loading, extracting, converting, manipulating, plotting and aggregating epidemiological parameters for infectious diseases. Epidemiological parameters extracted from the literature are loaded from the epiparameterDB R package.

This package provides simple functions to create constraints for small test assembly problems (e.g. van der Linden (2005, ISBN: 978-0-387-29054-6)) using sparse matrices. Currently, GLPK', lpSolve', Symphony', and Gurobi are supported as solvers. The gurobi package is not available from any mainstream repository; see <https://www.gurobi.com/downloads/>.

Fit models of modularity to morphological landmarks. Perform model selection on results. Fit models with a single within-module correlation or with separate within-module correlations fitted to each module.

Gas/Liquid Chromatography-Mass Spectrometer(GC/LC-MS) Data Analysis for Environmental Science. This package covered topics such molecular isotope ratio, matrix effects and Short-Chain Chlorinated Paraffins analysis etc. in environmental analysis.

Description: Application of empirical mode decomposition based support vector regression model for nonlinear and non stationary univariate time series forecasting. For method details see (i) Choudhury (2019) <http://krishi.icar.gov.in/jspui/handle/123456789/44873>; (ii) Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/43174>; (iii) Das (2023) <http://krishi.icar.gov.in/jspui/handle/123456789/77772>.

Use structural equation modeling to estimate average and conditional effects of a treatment variable on an outcome variable, taking into account multiple continuous and categorical covariates.

This package provides API access to data from the U.S. Energy Information Administration ('EIA') <https://www.eia.gov/>. Use of the EIA's API and this package requires a free API key obtainable at <https://www.eia.gov/opendata/register.php>. This package includes functions for searching the EIA data directory and returning time series and geoset time series datasets. Datasets returned by these functions are provided by default in a tidy format, or alternatively, in more raw formats. It also offers helper functions for working with EIA date strings and time formats and for inspecting different summaries of series metadata. The package also provides control over API key storage and caching of API request results.

Create causal models for use in epidemiological studies, including sufficient-component cause models as introduced by Rothman (1976) <doi:10.1093/oxfordjournals.aje.a112335>.

This package provides tools for exploratory analysis of tabular data using colour highlighting. Highlighting is displayed in any console supporting ANSI colours, and can be converted to HTML', typst', latex and SVG'. quarto and rmarkdown rendering are directly supported. It is also possible to add colour to regular expression matches and highlight differences between two arbitrary R objects.

This package provides a Shiny web application for energy industry analytics. Take an overview of the industry, measure Key Performance Indicators, identify changes in the industry over time, and discover new relationships in the data.

This package provides functions for treatment effect estimation, hypothesis testing, and future study design for settings where the surrogate is used in place of the primary outcome for individuals for whom the surrogate is valid, and the primary outcome is purposefully measured in the remaining patients. More details are available in: Knowlton, R., Parast, L. (2024) ``Efficient Testing Using Surrogate Information," Biometrical Journal, 67(6): e70086, <doi:10.1002/bimj.70086>. A tutorial for this package can be found at <https://www.laylaparast.com/etsi>.

This package provides a dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects. Johnson WE & Li C (2007) <doi:10.1093/biostatistics/kxj037> "Adjusting batch effects in microarray expression data using empirical Bayes methods." Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.11.024> "Harmonization of cortical thickness measurements across scanners and sites." Fortin J-P, Parker D, Tun<e7> B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.08.047> "Harmonization of multi-site diffusion tensor imaging data.".

Exploratory principal component analysis for large-scale dataset, including sparse principal component analysis and sparse matrix approximation.