Abstract
Simple features are a standardized way of encoding spatial vector data (points, lines, polygons) in computers.The sf package implements simple features in R, and has roughly the same capacity for spatial vector data as packages sp, rgeos, and rgdal.We describe the need for this package, its place in the R package ecosystem, and its potential to connect R to other computer systems.We illustrate this with examples of its use.
Keywords
Related Publications
Online Passive-Aggressive Algorithms
We present a unified view for online classification, regression, and uniclass problems. This view leads to a single algorithmic framework for the three problems. We prove worst ...
Adaptive Online Gradient Descent
We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori...
Practical Variational Inference for Neural Networks
Variational methods have been previously explored as a tractable approximation to Bayesian inference for neural networks. However the approaches proposed so far have only been a...
Keeping the neural networks simple by minimizing the description length of the weights
Article Keeping the neural networks simple by minimizing the description length of the weights Share on Authors: Geoffrey E. Hinton View Profile , Drew van Camp View Profile Aut...
Large Mass Hierarchy from a Small Extra Dimension
We propose a new higher-dimensional mechanism for solving the Hierarchy Problem. The Weak scale is generated from a large scale of order the Planck scale through an exponential ...
Publication Info
- Year
- 2018
- Type
- article
- Volume
- 10
- Issue
- 1
- Pages
- 439-439
- Citations
- 3985
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.32614/rj-2018-009