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GBOP2

Generalized Bayesian Optimal Phase II Design (G-BOP2)

Provides functions for implementing the Generalized Bayesian Optimal Phase II (G-BOP2) design using various Particle Swarm Optimization (PSO) algorithms, including: - PSO-Default, based on Kennedy and Eberhart (1995) <doi:10.1109/ICNN.1995.488968>, "Particle Swarm Optimization"; - PSO-Quantum, based on Sun, Xu, and Feng (2004) <doi:10.1109/ICCIS.2004.1460396>, "A Global Search Strategy of Quantum-Behaved Particle Swarm Optimization"; - PSO-Dexp, based on Stehlík et al. (2024) <doi:10.1016/j.asoc.2024.111913>, "A Double Exponential Particle Swarm Optimization with Non-Uniform Variates as Stochastic Tuning and Guaranteed Convergence to a Global Optimum with Sample Applications to Finding Optimal Exact Designs in Biostatistics"; - and PSO-GO.

Versions across snapshots

VersionRepositoryFileSize
0.1.4 rolling source/ R- GBOP2_0.1.4.tar.gz 687.6 KiB
0.1.4 rolling linux/jammy R-4.5 GBOP2_0.1.4.tar.gz 990.4 KiB
0.1.4 latest source/ R- GBOP2_0.1.4.tar.gz 687.6 KiB
0.1.4 latest linux/jammy R-4.5 GBOP2_0.1.4.tar.gz 990.4 KiB
0.1.4 2026-04-23 source/ R- GBOP2_0.1.4.tar.gz 687.6 KiB
0.1.4 2026-04-09 windows/windows R-4.5 GBOP2_0.1.4.zip 1.2 MiB
0.1.2 2025-04-20 source/ R- GBOP2_0.1.2.tar.gz 400.5 KiB

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