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: |
0.1.2 |
| 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: |
2025-04-09 |
| DOI: |
10.32614/CRAN.package.GBOP2 |
| Author: |
Xinying Fang [aut],
Wanni Lei [aut, cre] |
| Maintainer: |
Wanni Lei <wanni.lei17 at gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
GBOP2 results |
Documentation:
Downloads:
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