Boptbd-internal: Internal function

In Boptbd: Bayesian Optimal Block Designs

Description

This function is for internal usage only

Usage

 
## 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)

Arguments

trt.N	integer, specifying number of treatments, v.
blk.N	integer, specifying number of arrays, b.
alpha	numeric, representing shape parameter of beta distribution.
beta	numeric, representing shape parameter of beta distribution.
nrep	integer, specifying number of replications of the optimization procedure.
brep	integer, specifying number of Monte Carlo samples from a prior beta distribution, Beta(alpha, beta).
itr.cvrgval	integer, specifying number of iterations required for convergence during the exchange procedure. See Boptbd documentation for details.

Details

These functions are handled via a generic function Boptbd. Please refer to the Boptbd documentation for details.

Author(s)

Dibaba Bayisa Gemechu, Legesse Kassa Debusho, and Linda Haines

References

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.

See Also

Boptbd

Boptbd documentation built on March 26, 2020, 8:38 p.m.