Simple Features for R

Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.

Display and Analyze ROC Curves

Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

Create and Investigate Magic Squares

A collection of functions for the manipulation and analysis of arbitrarily dimensioned arrays. The original motivation for the package was the development of efficient, vectorized algorithms for the creation and investigation of magic squares and high-dimensional magic hypercubes.

Wrapper for the Gnu Scientific Library

An R wrapper for some of the functionality of the Gnu Scientific Library.

Manipulate and Map Origin-Destination Data

The aim of 'od' is to provide tools and example datasets for working with origin-destination ('OD') datasets of the type used to describe aggregate urban mobility patterns (Carey et al. 1981) . The package builds on functions for working with 'OD' data in the package 'stplanr', (Lovelace and Ellison 2018) with a focus on computational efficiency and support for the 'sf' class system (Pebesma 2018) . With few dependencies and a simple class system based on data frames, the package is intended to facilitate efficient analysis of 'OD' datasets and to provide a place for developing new functions. The package enables the creation and analysis of geographic entities representing large scale mobility patterns, from daily travel between zones in cities to migration between countries.

Thematic Maps

Thematic maps are geographical maps in which spatial data distributions are visualized. This package offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.

Datasets for Spatial Analysis

Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON and GeoPackage, but from version 2.3.4, no longer ESRI Shapefile - use GeoPackage instead. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques.

The Gauss Hypergeometric Function

The Gaussian hypergeometric function for complex numbers.

Propensity to Cycle Tool

Functions and example data to teach and increase the reproducibility of the methods and code underlying the Propensity to Cycle Tool (PCT), a research project and web application hosted at < https://www.pct.bike/>. For an academic paper on the methods, see Lovelace et al (2017) .

Very Large Numbers in R

Very large numbers in R. Real numbers are held using their natural logarithms, plus a logical flag indicating sign. Functionality for complex numbers is also provided. The package includes a vignette that gives a step-by-step introduction to using S4 methods.