The Ultimate Guide to the matchingR Package in R
Explore valuable documentation and insights to make the most of the matchingR package in R. Get ready to unlock the full potential of the matchingR package!
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What is the matchingR package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The matchingR package is a tool for finding optimal matchings in bipartite graphs, a common problem in fields such as operations research and computer science. It implements the Hungarian algorithm, a powerful technique for this type of problem.
- Title: Matching Algorithms in R and C++
- Description: Computes matching algorithms quickly using Rcpp. Implements the Gale-Shapley Algorithm to compute the stable matching for two-sided markets, such as the stable marriage problem and the college-admissions problem. Implements Irving's Algorithm for the stable roommate problem. Implements the top trading cycle algorithm for the indivisible goods trading problem.
- Author: Jan Tilly, Nick Janetos
- Maintainer: Jan Tilly
How to install the matchingR package?
In this section, we’ll walk you through the process of installing and loading the matchingR package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.
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What package information should you know?
In this section, we’ll go over the technical aspects of the matchingR package.
Key features
- Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify built-in datasets. To identify the datasets for the matchingR package, visit our database of R datasets.
- Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes for the matchingR package, you can visit our visit our database of R vignettes.
- Citation: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find citation information for the matchingR package, visit our database of R package citations.
Technical details
- License type: GPL (>= 2). For license details, visit the Open Source Initiative website.
- Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The matchingR package has compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The matchingR package has the following required dependencies: Rcpp.
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The matchingR package has the following suggested dependencies: testthat, knitr, rmarkdown.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The matchingR package uses the following external sources: Rcpp, RcppArmadillo.
- Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The matchingR package has no imported packages.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The matchingR package has no enhancements.
How to get help with the matchingR package?
In this section, we’ll discuss a variety of available resources for getting help with the matchingR package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("matchingR") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
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Package website: The matchingR package has a dedicated website. You can visit: https://github.com/jtilly/matchingR/.
- Developer support: You can email Jan Tilly . For contact information, visit our R community directory.
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- Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.
Other package guides
Explore our comprehensive guides for other R packages. These guides are valuable resources for accessing a wide range of information, making it easier to navigate R documentation in one place.
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