This software downloads and manages air quality data from the European Environmental Agency (EEA) dataflow (<https://www.eea.europa.eu/data-and-maps/data/aqereporting-9>). See the web page <https://eeadmz1-downloads-webapp.azurewebsites.net/> for details on the EEA's Air Quality Download Service. The package allows dynamically mapping the stations, summarising and time aggregating the measurements and building spatial interpolation maps. See the web page <https://www.eea.europa.eu/en> for further information on EEA activities and history. Further details, as well as, an extended vignette of the main functions included in the package, are available at the GitHub web page dedicated to the project.

This package provides a wrapper of different methods from Linear Algebra for the equations introduced in The Atlas of Economic Complexity and related literature. This package provides standard matrix and graph output that can be used seamlessly with other packages. See <doi:10.21105/joss.01866> for a summary of these methods and its evolution in literature.

This package provides a system to facilitate designing comparative (and non-comparative) experiments using the grammar of experimental designs <https://emitanaka.org/edibble-book/>. An experimental design is treated as an intermediate, mutable object that is built progressively by fundamental experimental components like units, treatments, and their relation. The system aids in experimental planning, management and workflow.

Calculates the (approximate) effective number of clusters for a regression model, as described in Carter, Schnepel, and Steigerwald (2017) <doi:10.1162/REST_a_00639>. The effective number of clusters is a statistic to assess the reliability of asymptotic inference when sampling or treatment assignment is clustered. Methods are implemented for stats::lm(), plm::plm(), and fixest::feols(). There is also a formula method.

This package provides a consistent representation of year-based time scales as a numeric vector with an associated era'. There are built-in era definitions for many year numbering systems used in contemporary and historic calendars (e.g. Common Era, Islamic Hijri years); year-based time scales used in archaeology, astronomy, geology, and other palaeosciences (e.g. Before Present, SI-prefixed annus'); and support for arbitrary user-defined eras. Years can converted from any one era to another using a generalised transformation function. Methods are also provided for robust casting and coercion between years and other numeric types, type-stable arithmetic with years, and pretty-printing in tables.

It allows you to automatically monitor trends of social media messages by time, place and topic aiming at detecting public health threats early through the detection of signals (i.e., an unusual increase in the number of messages per time, topic and location). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords. More information on the original package epitweetr is available in the peer-review publication Espinosa et al. (2022) <doi:10.2807/1560-7917.ES.2022.27.39.2200177>.

Interconverts between ordered lists and compact string notation. Useful for capturing code lists, and pair-wise codes and decodes, for text storage. Analogous to factor levels and labels. Generics encode() and decode() perform interconversion, while codes() and decodes() extract components of an encoding. The function encoded() checks whether something is interpretable as an encoding. If a vector has an encoded guide attribute, as_factor() uses it to coerce to factor.

Structure mining from XGBoost and LightGBM models. Key functionalities of this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable importance, measuring of interaction importance, explanation of single prediction with break down plots (based on xgboostExplainer and iBreakDown packages). To download the LightGBM use the following link: <https://github.com/Microsoft/LightGBM>. EIX is a part of the DrWhy.AI universe.

Evaluates the empirical characteristic function of univariate and multivariate samples. This package uses RcppArmadillo for fast evaluation. It is also possible to export the code to be used in other packages at C++ level.

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>.

Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.

By overloading the R help() function, this package allows users to use "docstring" style comments within their own defined functions. The package also provides additional functions to mimic the R basic example() function and the prototyping of packages.

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

Package provides a set of tools for robust estimation and inference for probit model with endogenous covariates. The current version contains a robust two-step estimator. For technical details, see Naghi, Varadi and Zhelonkin (2022), <doi:10.1016/j.ecosta.2022.05.001>.

Unofficial API wrapper for Euroleague and Eurocup basketball API (<https://www.euroleaguebasketball.net/en/euroleague/>), it allows to retrieve real-time and historical standard and advanced statistics about competitions, teams, players and games.

Endpoint selection and sample size reassessment for multiple binary endpoints based on blinded and/or unblinded data. Trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation between endpoints. The implemented design is proposed in Bofill Roig, M., Gómez Melis, G., Posch, M., and Koenig, F. (2022). <doi:10.48550/arXiv.2206.09639>.

Descriptive analysis is essential for publishing medical articles. This package provides an easy way to conduct the descriptive analysis. 1. Both numeric and factor variables can be handled. For numeric variables, normality test will be applied to choose the parametric and nonparametric test. 2. Both two or more groups can be handled. For groups more than two, the post hoc test will be applied, Tukey for the numeric variables and FDR for the factor variables. 3. T test, ANOVA or Fisher test can be forced to apply. 4. Mean and standard deviation can be forced to display.

Construct the admissible exact intervals for the binomial proportion, the Poisson mean and the total number of subjects with a certain attribute or the total number of the subjects for the hypergeometric distribution. Both one-sided and two-sided intervals are of interest. This package can be used to calculate the intervals constructed methods developed by Wang (2014) <doi:10.5705/ss.2012.257> and Wang (2015) <doi:10.1111/biom.12360>.

This package implements two estimations related to the foundations of info metrics applied to ecological inference. These methodologies assess the lack of disaggregated data and provide an approach to obtaining disaggregated territorial-level data. For more details, see the following references: Fernández-Vázquez, E., Dà az-Dapena, A., Rubiera-Morollón, F. et al. (2020) "Spatial Disaggregation of Social Indicators: An Info-Metrics Approach." <doi:10.1007/s11205-020-02455-z>. Dà az-Dapena, A., Fernández-Vázquez, E., Rubiera-Morollón, F., & Vinuela, A. (2021) "Mapping poverty at the local level in Europe: A consistent spatial disaggregation of the AROPE indicator for France, Spain, Portugal and the United Kingdom." <doi:10.1111/rsp3.12379>.

Exploring time series for signal detection. It is specifically designed to detect possible outbreaks using infectious disease surveillance data at the European Union / European Economic Area or country level. Automatic detection tools used are presented in the paper "Monitoring count time series in R: aberration detection in public health surveillance", by Salmon (2016) <doi:10.18637/jss.v070.i10>. The package includes: - Signal Detection tool, an interactive shiny application in which the user can import external data and perform basic signal detection analyses; - An automated report in HTML format, presenting the results of the time series analysis in tables and graphs. This report can also be stratified by population characteristics (see Population variable). This project was funded by the European Centre for Disease Prevention and Control.

Support functions for R-based EQUAL-STATS software which automatically classifies the data and performs appropriate statistical tests. EQUAL-STATS software is a shiny application with an user-friendly interface to perform complex statistical analysis. Gurusamy,K (2024)<doi:10.5281/zenodo.13354162>.

This package provides a meta-package that installs and loads a set of packages from easystats ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, visualization, and reporting. Additionally, it provides articles targeted at instructors for teaching easystats', and a dashboard targeted at new R users for easily conducting statistical analysis by accessing summary results, model fit indices, and visualizations with minimal programming.

Implementation of uniformly most powerful invariant equivalence tests for one- and two-sample problems (paired and unpaired) as described in Wellek (2010, ISBN:978-1-4398-0818-4). Also one-sided alternatives (non-inferiority and non-superiority tests) are supported. Basically a variant of a t-test with (relaxed) null and alternative hypotheses exchanged.

Fast and memory-less computation of the energy statistics related quantities for vectors and matrices. References include: Szekely G. J. and Rizzo M. L. (2014), <doi:10.1214/14-AOS1255>. Szekely G. J. and Rizzo M. L. (2023), <ISBN:9781482242744>. Tsagris M. and Papadakis M. (2025). <doi:10.48550/arXiv.2501.02849>.