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RLoptimal

Optimal Adaptive Allocation Using Deep Reinforcement Learning

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.

Versions across snapshots

VersionRepositoryFileSize
1.2.2 rolling linux/jammy R-4.5 RLoptimal_1.2.2.tar.gz 246.3 KiB
1.2.2 rolling linux/noble R-4.5 RLoptimal_1.2.2.tar.gz 246.2 KiB
1.2.2 rolling source/ R- RLoptimal_1.2.2.tar.gz 137.1 KiB
1.2.2 latest linux/jammy R-4.5 RLoptimal_1.2.2.tar.gz 246.3 KiB
1.2.2 latest linux/noble R-4.5 RLoptimal_1.2.2.tar.gz 246.2 KiB
1.2.2 latest source/ R- RLoptimal_1.2.2.tar.gz 137.1 KiB
1.2.2 2026-04-26 source/ R- RLoptimal_1.2.2.tar.gz 137.1 KiB
1.2.2 2026-04-23 source/ R- RLoptimal_1.2.2.tar.gz 137.1 KiB
1.2.2 2026-04-09 windows/windows R-4.5 RLoptimal_1.2.2.zip 252.3 KiB
1.2.1 2025-04-20 source/ R- RLoptimal_1.2.1.tar.gz 137.1 KiB

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