Airport problems, introduced by Littlechild and Owen (1973) <https://www.jstor.org/stable/2629727>, are cost allocation problems where agents share the cost of a facility (or service) based on their ordered needs. Valid allocations must satisfy no-subsidy constraints, meaning that no group of agents contributes more than the highest cost of its members (i.e., no agent is allowed to subsidize another). A rule is a mechanism that selects an allocation vector for a given problem. This package computes several rules proposed in the literature, including both standard rules and their variants, such as weighted versions, rules for clones, and rules based on the agentsâ hierarchy order. These rules can be applied to various problems of interest, including the allocation of liabilities and the maintenance of irrigation systems, among others. Moreover, the package provides functions for graphical representation, enabling users to visually compare the outcomes produced by each rule, or to display the no-subsidy set. In addition, it includes four datasets illustrating different applications and examples of airport problems. For a more detailed explanation of all concepts, see Thomson (2024) <doi:10.1016/j.mathsocsci.2024.03.007>.

In fields such as ecology, microbiology, and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis (PCoA) is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide aPCoA as an easy-to-use tool to improve data visualization in this context, enabling enhanced presentation of the effects of interest. Details are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine Peterson and Robert Jenq (2020) Bioinformatics, Volume 36, Issue 13, 4099-4101.

The transmission between two time-series prices is assessed. It contains several functions for linear and nonlinear threshold co-integration, and furthermore, symmetric and asymmetric error correction models.

Process results generated by Antares', a powerful open source software developed by RTE (Réseau de Transport dâ à lectricité) to simulate and study electric power systems (more information about Antares here: <https://github.com/AntaresSimulatorTeam/Antares_Simulator>). This package provides functions to create new columns like net load, load factors, upward and downward margins or to compute aggregated statistics like economic surpluses of consumers, producers and sectors.

Examples of datasets on allometry, the study of the relationship of biological traits to body size. This package contains the datasets of morphological measurement taken from 113 maritime earwigs (Anisolabis maritima) by Matsuzawa and Konuma (2025) <doi:10.1093/biolinnean/blaf031>, and taken from 507 Helmâ s stag beetles (Geodorcus helmsi) collected by Grey et al. (2025) <doi:10.1093/biolinnean/blae024>.

All animal behaviour occurs sequentially. The package has a number of functions to format sequence data from different sources, to analyse sequential behaviour and communication in animals. It also has functions to plot the data and to calculate the entropy of sequences.

Implementation in R of the alpha-shape of a finite set of points in the three-dimensional space. The alpha-shape generalizes the convex hull and allows to recover the shape of non-convex and even non-connected sets in 3D, given a random sample of points taken into it. Besides the computation of the alpha-shape, this package provides users with functions to compute the volume of the alpha-shape, identify the connected components and facilitate the three-dimensional graphical visualization of the estimated set.

The empirical cumulative average deviation function introduced by the author is utilized to develop both Ad- and Ud-plots. The Ad-plot can identify symmetry, skewness, and outliers of the data distribution, including anomalies. The Ud-plot created by slightly modifying Ad-plot is exceptional in assessing normality, outperforming normal QQ-plot, normal PP-plot, and their derivations. The d-value that quantifies the degree of proximity between the Ud-plot and the graph of the estimated normal density function helps guide to make decisions on confirmation of normality. Full description of this methodology can be found in the article by Wijesuriya (2025) <doi:10.1080/03610926.2024.2440583>.

This package provides a developer-facing interface to the Arrow Database Connectivity ('ADBC') PostgreSQL driver for the purposes of building high-level database interfaces for users. ADBC <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses Arrow for result sets and query parameters.

Fit pharmacokinetic/pharmacodynamic (PK/PD) models to aggregate-level data (mean vector and covariance matrix per study) rather than individual-level data, for meta-analysis across studies. Integrates with the nlmixr2'/'rxode2 ecosystem via four estimation methods: a First-Order ('FO') analytical estimator, a Monte Carlo (MC) estimator, a Gauss-Hermite quadrature ('GH') estimator, and an Iterative Reweighting Monte Carlo ('IRMC') estimator. Methods are based on Välitalo (2021) <doi:10.1007/s10928-021-09760-1>; software described in van de Beek et al. (2025) <doi:10.1007/s10928-025-10011-w>.

Providing the functions for communicating with Amazon Web Services(AWS) Elastic Compute Cloud(EC2) and Elastic Container Service(ECS). The functions will have the prefix ecs_ or ec2_ depending on the class of the API. The request will be sent via the REST API and the parameters are given by the function argument. The credentials can be set via aws_set_credentials'. The EC2 documentation can be found at <https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Welcome.html> and ECS can be found at <https://docs.aws.amazon.com/AmazonECS/latest/APIReference/Welcome.html>.

The ArcGIS Places service is a ready-to-use location service that can search for businesses and geographic locations around the world. It allows you to find, locate, and discover detailed information about each place. Query for places near a point, within a bounding box, filter based on categories, or provide search text. arcgisplaces integrates with sf for out of the box compatibility with other spatial libraries. Learn more in the Places service API reference <https://developers.arcgis.com/rest/places/>.

Fetch Australian Taxation Office (ATO) Taxation Statistics and related datasets via the data.gov.au Comprehensive Knowledge Archive Network ('CKAN') API <https://data.gov.au/data/api/3/>. Provides tidy access to individual, company, superannuation, goods and services tax (GST), fringe benefits tax (FBT), Voluntary Tax Transparency Code (VTTC), Pay As You Go (PAYG) withholding, charity, excise, and Corporate Tax Transparency data, plus Petroleum Resource Rent Tax, Medicare Levy Surcharge, and fuel tax credit aggregates. Includes reproducibility helpers (snapshot pinning, SHA-256 cache integrity, session manifest, optional Zenodo deposit), classification crosswalks (ANZSIC 2006 to 2020, ANZSCO 2013 to 2021), panel harmonisation, reconciliation against Final Budget Outcome totals, and real-terms and per-capita helpers backed by bundled Australian Bureau of Statistics (ABS) Consumer Price Index and Estimated Resident Population series. Bridges to the taxstats 2 per cent microdata sample via column-schema mapping. Data is published by the Australian Taxation Office under Creative Commons Attribution 2.5 Australia or 3.0 Australia licences (dataset-dependent).

Allows you to connect to an Alfresco content management repository and interact with its contents using simple and intuitive functions. You will be able to establish a connection session to the Alfresco repository, read and upload content and manage folder hierarchies. For more details on the Alfresco content management repository see <https://www.alfresco.com/ecm-software/document-management>.

This package provides R bindings to the Automerge Conflict-free Replicated Data Type ('CRDT') library. Automerge enables automatic merging of concurrent changes without conflicts, making it ideal for distributed systems, collaborative applications, and offline-first architectures. The approach of local-first software was proposed in Kleppmann, M., Wiggins, A., van Hardenberg, P., McGranaghan, M. (2019) <doi:10.1145/3359591.3359737>. This package supports all Automerge data types (maps, lists, text, counters) and provides both low-level and high-level synchronization protocols for seamless interoperability with JavaScript and other Automerge implementations.

This package implements the allan variance and allan variance linear regression estimator for latent time series models. More details about the method can be found, for example, in Guerrier, S., Molinari, R., & Stebler, Y. (2016) <doi:10.1109/LSP.2016.2541867>.

Create APA style text from analyses for use within R Markdown documents. Descriptive statistics, confidence intervals, and cell sizes are reported.

This package provides a comprehensive toolkit for astronomical and cosmological computations. Provides functions for angular coordinate conversions (degrees, hours-minutes-seconds, degrees-minutes-seconds, and radians), access to fundamental physical constants, queries to the Gaia Archive TAP (Table Access Protocol) service, cosmological distance calculations, early-universe thermal physics including photon density, Saha equation solutions, and a full thermal-cosmology module covering the Hubble rate in the radiation-dominated era, effective relativistic degrees of freedom, entropy density, equilibrium yields, the Boltzmann relic-abundance ('pebble') equation for WIMP freeze-out, the freeze-out temperature solver, and the Peebles equation for hydrogen recombination. Also includes the Drake equation for estimating the number of communicating extraterrestrial civilisations in the Milky Way.

This package provides an automatic aggregation tool to manage point data privacy, intended to be helpful for the production of official spatial data and for researchers. The package pursues the data accuracy at the smallest possible areas preventing individual information disclosure. The methodology, based on hierarchical geographic data structures performs aggregation and local suppression of point data to ensure privacy as described in Lagonigro, R., Oller, R., Martori J.C. (2017) <doi:10.2436/20.8080.02.55>. The data structures are created following the guidelines for grid datasets from the European Forum for Geography and Statistics.

Estimate the linear and nonlinear autoregressive distributed lag (ARDL & NARDL) models and the corresponding error correction models, and test for longrun and short-run asymmetric. The general-to-specific approach is also available in estimating the ARDL and NARDL models. The Pesaran, Shin & Smith (2001) (<doi:10.1002/jae.616>) bounds test for level relationships is also provided. The ardl.nardl package also performs short-run and longrun symmetric restrictions available at Shin et al. (2014) <doi:10.1007/978-1-4899-8008-3_9> and their corresponding tests.

Wraps dplyr verbs (mutate, summarise, filter) to automatically capture variable metadata (type, source columns, categories, and source code), producing a codebook and eligibility tracking table with zero manual documentation. Works with both sparklyr (tbl_spark) and local data frames. Adds big-data optimizations (caching, assume-unique counting, checkpointing) and a standardized report module with an eligibility flowchart, editable codebook export (HTML, DOCX, XLSX), and cross-sectional or longitudinal variable inspection. The eligibility flowchart follows the CONSORT statement (Schulz, Altman and Moher (2010) <doi:10.1136/bmj.c332>) and the reporting of observational cohort studies follows the STROBE recommendations (von Elm and others (2007) <doi:10.1371/journal.pmed.0040296>).

Wraps the AT Protocol (Authenticated Transfer Protocol) behind Bluesky <https://bsky.social>. Functions can be used for, among others, retrieving posts and followers from the network or posting content.

This package provides tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.

Automated methods to assemble population PK (pharmacokinetic) and PKPD (pharmacodynamic) datasets for analysis in NONMEM (non-linear mixed effects modeling) by Bauer (2019) <doi:10.1002/psp4.12404>. The package includes functions to build datasets from SDTM (study data tabulation module) <https://www.cdisc.org/standards/foundational/sdtm>, ADaM (analysis dataset module) <https://www.cdisc.org/standards/foundational/adam>, or other dataset formats. The package will combine population datasets, add covariates, and create documentation to support regulatory submission and internal communication.