Generalized Bayesian Optimal Phase II Design (G-BOP2)
PSOGO: Power maximizing design with dual boundaries
PSOGO: Power maximizing design with single boundary for futility
PSOGO: Power maximizing design with efficacy and toxicity boundaries
PSOGO: Optimal/Minimax design with dual boundaries
PSOGO: Optimal/Minimax design with single boundary for futility
PSOGO: Optimal/Minimax design with efficacy and toxicity boundaries
Get current cluster
Initialize parallel cluster
Stop and clean up the cluster
Summary function Summary function for gbop2 objects
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.