This function is for internal usage only
## Computes Bayesian A-optimal block designs
## using block/array exchange algorithm
Baoptbd(trt.N, blk.N, alpha, beta, nrep, brep, itr.cvrgval)
## Computes Bayesian D-optimal block designs
## using block/array exchange algorithm
Bdoptbd(trt.N, blk.N, alpha, beta, nrep, brep, itr.cvrgval)integer, specifying number of treatments, v.
integer, specifying number of arrays, b.
numeric, representing shape parameter of beta distribution.
numeric, representing shape parameter of beta distribution.
integer, specifying number of replications of the optimization procedure.
integer, specifying number of Monte Carlo samples from a prior beta distribution, Beta(alpha, beta).
integer, specifying number of iterations required for convergence during the exchange procedure. See Boptbd documentation for details.
These functions are handled via a generic function Boptbd. Please refer to the Boptbd documentation for details.
Debusho, L. K., Gemechu, D. B. and Haines, L. (2018). Algorithmic construction of optimal block designs for two-colour cDNA microarray experiments using the linear mixed effects model. Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/03610918.2018.1429617.
Gemechu D. B., Debusho L. K. and Haines L. M. (2014). A-optimal designs for two-colour cDNA microarray experiments using the linear mixed effects model. Peer-reviewed Proceedings of the Annual Conference of the South African Statistical Association for 2014 (SASA 2014), Rhodes University, Grahamstown, South Africa. pp 33-40, ISBN: 978-1-86822-659-7.