The Ultimate Guide to the rsm Package in R
Explore valuable documentation and insights to make the most of the rsm package in R. Get ready to unlock the full potential of the rsm package!
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What is the rsm package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The rsm package, short for Response Surface Methods, is a package for the design and analysis of experiments for optimizing response surfaces and exploring fitted surfaces. It’s typically employed in industrial and systems engineering.
- Title: Response-Surface Analysis
- Description: Provides functions to generate response-surface designs, fit first- and second-order response-surface models, make surface plots, obtain the path of steepest ascent, and do canonical analysis. A good reference on these methods is Chapter 10 of Wu, C-F J and Hamada, M (2009) "Experiments: Planning, Analysis, and Parameter Design Optimization" ISBN 978-0-471-69946-0. An early version of the package is documented in Journal of Statistical Software .
- Author: Russell Lenth [aut, cre]
- Maintainer: Russell Lenth
How to install the rsm package?
In this section, we’ll walk you through the process of installing and loading the rsm 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 rsm 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 rsm 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 rsm 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 rsm 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 rsm package does not have compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The rsm package has no required dependencies.
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The rsm package has the following suggested dependencies: emmeans (> 1.3.5.1), Vdgraph, conf.design, DoE.base, FrF2.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The rsm package does not use any external sources.
- Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The rsm package has the following imported packages: estimability.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The rsm package has no enhancements.
How to get help with the rsm package?
In this section, we’ll discuss a variety of available resources for getting help with the rsm package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("rsm") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
-
Package website: The rsm package does not have a dedicated website.
- Developer support: You can email Russell Lenth . For contact information, visit our R community directory.
Additional resources
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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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