Abstract
The programming language S has a long history and increased its popularity amongst statisticians especially with the advent of its free software dialect R during the last decade. One key advantage of R is its extensibility by means of add-on packages which resulted in more than 5,000 packages available at present. Only a few of these packages are dedicated to design of experiments leaving several methods unimplemented. An attempt to fill some of these gaps regarding optimal design is made in Rasch et al. (Optimal experimental design with R. Chapman and Hall/CRC, Boca Raton, 2011) with its accompanying OPDOE library. While first versions of that library focused on getting the implementation of the algorithms done a new version with a somewhat simplified interface and improvements will be presented. The functions in the OPDOE library cover several topics of experimental design, including simple statistical tests, regression models, tests in analysis of variance models and sequential testing. The capabilities of the presented R library will be shown by a collection of examples covering these topics.
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Notes
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Comprehensive R Archive Network, http://cran.r-project.org, the central web archive of the R language.
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Acknowledgements
Thanks go to the co-authors of [3], Minghui Whang, who wrote most of the ANOVA functions, and Petr Simeček who wrote the initial version of the library.
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Gebhardt, A. (2014). Design of Experiments Using R. In: Melas, V., Mignani, S., Monari, P., Salmaso, L. (eds) Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2104-1_21
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DOI: https://doi.org/10.1007/978-1-4939-2104-1_21
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