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.
| Version: | 0.1.3 | 
| Depends: | R (≥ 4.1.0) | 
| Imports: | tidyr, R6, Rcpp, doParallel, foreach, dplyr, stats, globpso, parallel, utils, RcppArmadillo | 
| LinkingTo: | Rcpp, RcppArmadillo, RcppEigen | 
| Suggests: | knitr, rmarkdown, roxygen2, testthat (≥ 3.0.0), R.rsp | 
| Published: | 2025-04-22 | 
| DOI: | 10.32614/CRAN.package.GBOP2 | 
| Author: | Xinying Fang [aut],
  Wanni Lei [aut, cre],
  Shouhao Zhou [aut] | 
| Maintainer: | Wanni Lei  <wanni.lei17 at gmail.com> | 
| License: | GPL-2 | 
| NeedsCompilation: | yes | 
| CRAN checks: | GBOP2 results | 
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