An implementation to compute an optimal adaptive allocation rule using deep reinforcement learning in a dose-response study (Matsuura et al. (2022) <doi:10.1002/sim.9247>). The adaptive allocation rule can directly optimize a performance metric, such as power, accuracy of the estimated target dose, or mean absolute error over the estimated dose-response curve.
Version: 1.2.1 Imports: DoseFinding, glue, R6, reticulate, stats, utils Suggests: knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2025-01-13 DOI: 10.32614/CRAN.package.RLoptimal Author: Kentaro Matsuura [aut, cre, cph], Koji Makiyama [aut, ctb] Maintainer: Kentaro Matsuura <matsuurakentaro55 at gmail.com> BugReports: https://github.com/MatsuuraKentaro/RLoptimal/issues License: MIT + file LICENSE URL: https://github.com/MatsuuraKentaro/RLoptimal NeedsCompilation: no Language: en-US Materials: README NEWS CRAN checks: RLoptimal results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=RLoptimal to link to this page.
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