DiscrimUnifApproxT: Hybrid Algorithm of PSO and L-BFGS for Finding Optimal...

In PingYangChen/DiscrimOD: DiscrimOD: Finding Optimal Discrimination Designs by Hybridizing Particle Swarm and L-BFGS Algorithms

Description

Implement the hybridized PSO algorithm to find the optimal discrimination designs for 2 or more than 2 competing models

Usage

DiscrimUnifApproxT(MODEL_INFO, nSupp, dsLower, dsUpper, REMES_MAXIT = 50,
  REMES_FreeRun = 1, REMES_EPS = 0.001, LBFGS_INFO = NULL,
  seed = NULL, verbose = TRUE, environment, ...)

References

Atkinson, A. C. and Fedorov, V. V. (1975a). The design of experiments for discriminating between two rival models. Biometrika, 62(1):57-70.

Lopez-Fidalgo, J., Tommasi, C., and Trandafir, P. C. (2007). An optimal experimental design criterion for discriminating between non-normal models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69(2):231-242.

PingYangChen/DiscrimOD documentation built on Jan. 30, 2022, 5:25 p.m.