Read Australian Agricultural Data from Government Agencies

Downloads and imports agricultural data from the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) < https://www.agriculture.gov.au/abares> and the Australian Bureau of Statistics (ABS) < https://www.abs.gov.au>. Supports multiple data formats including spreadsheets, comma‑separated value (CSV) files, and geospatial data such as shapefiles and GeoTIFFs. Covers topics such as broadacre crops, livestock, soils, commodities and related agricultural information. The package standardises field names and data formats to improve interoperability and simplify analysis. It also streamlines the import of geospatial data and corrects common issues found in these data sources upon loading.

Calculate Slopes of Roads, Rivers and Trajectories

Calculates the slope (longitudinal gradient or steepness) of linear geographic features such as roads (for more details, see Ariza-López et al. (2019) ) and rivers (for more details, see Cohen et al. (2018) ). It can use local Digital Elevation Model (DEM) data or download DEM data via the 'ceramic' package. The package also provides functions to add elevation data to linestrings and visualize elevation profiles.

Construct Reproducible Analytic Data Sets as R Packages

A framework to help construct R data packages in a reproducible manner. Potentially time consuming processing of raw data sets into analysis ready data sets is done in a reproducible manner and decoupled from the usual 'R CMD build' process so that data sets can be processed into R objects in the data package and the data package can then be shared, built, and installed by others without the need to repeat computationally costly data processing. The package maintains data provenance by turning the data processing scripts into package vignettes, as well as enforcing documentation and version checking of included data objects. Data packages can be version controlled on 'GitHub', and used to share data for manuscripts, collaboration and reproducible research.

Evaluate Clinical Prediction Models by Net Monetary Benefit

Estimates when and where a model-guided treatment strategy may outperform a treat-all or treat-none approach by Monte Carlo simulation and evaluation of the Net Monetary Benefit. Details can be viewed in Parsons et al. (2023) .

Parse Messy Geographic Coordinates

Parse messy geographic coordinates from various character formats to decimal degree numeric values. Parse coordinates into their parts (degree, minutes, seconds); calculate hemisphere from coordinates; pull out individually degrees, minutes, or seconds; add and subtract degrees, minutes, and seconds. C++ code herein originally inspired from code written by Jeffrey D. Bogan, but then completely re-written.

Accesses Weather Data from the Iowa Environment Mesonet

Allows to get weather data from Automated Surface Observing System (ASOS) stations (airports) in the whole world thanks to the Iowa Environment Mesonet website.

'Microsoft Academic' API Client

The 'Microsoft Academic Knowledge' API provides programmatic access to scholarly articles in the 'Microsoft Academic Graph' (< https://academic.microsoft.com/>). Includes methods matching all 'Microsoft Academic' API routes, including search, graph search, text similarity, and interpret natural language query string.

NASA POWER API Client

An API client for NASA POWER global meteorology, surface solar energy and climatology data API. POWER (Prediction Of Worldwide Energy Resources) data are freely available for download with varying spatial resolutions dependent on the original data and with several temporal resolutions depending on the POWER parameter and community. This work is funded through the NASA Earth Science Directorate Applied Science Program. For more on the data themselves, the methodologies used in creating, a web-based data viewer and web access, please see < https://power.larc.nasa.gov/>.

Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via 'XML'

Setup, run and analyze 'NetLogo' (< https://www.netlogo.org>) model simulations in 'R'. 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. The user defines all information that is needed in an intuitive framework, using class objects. Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. This also enables simulating 'NetLogo' experiments on remote high performance computing machines. In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.

Recodes Sex/Gender Descriptions into a Standard Set

Provides dictionary-based tools for recoding free-text gender responses into consistent categories while preserving gender diversity where possible. The package standardises spelling, capitalization, whitespace, and common variants through curated named character-vector dictionaries, supports either detailed or collapsed output categories, and can retain original unmatched responses for manual review. It also includes helpers for creating custom dictionaries from approximate string matches and a local interactive application for recoding uploaded data files.