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optbdmaeAT (version 1.0.1)

optbdmaeAT-internal: Internal functions

Description

Functions for internal usage only.

Usage

## Computes A-optimal or near-optimal block designs
## using array exchange algorithm
Aoptbd.maeA(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes A-optimal or near-optimal block designs
## using treatment exchange algorithm
Aoptbd.maeT(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes MV-optimal or near-optimal block designs
## using array exchange algorithm
MVoptbd.maeA(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes MV-optimal or near-optimal block designs
## using treatment exchange algorithm
MVoptbd.maeT(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes D-optimal or near-optimal block designs
## using array exchange algorithm
Doptbd.maeA(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes D-optimal or near-optimal block designs
## using treatment exchange algorithm
Doptbd.maeT(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes E-optimal or near-optimal block designs
## using array exchange algorithm
Eoptbd.maeA(trt.N, blk.N, theta, nrep, itr.cvrgval) 
## Computes E-optimal or near-optimal block designs
## using treatment exchange algorithm
Eoptbd.maeT(trt.N, blk.N, theta, nrep, itr.cvrgval)

Arguments

trt.N
integer, specifying number of treatments, v.
blk.N
integer, specifying number of arrays, b.
theta
numeric, representing a function of the ratio of random array variance and random error variance. It takes any value between 0 and 1, inclusive.
nrep
integer, specifying number of replications of the optimization procedure.
itr.cvrgval
integer, specifying number of iterations required for convergence during the exchange procedure. See optbdmaeAT documentation for details.

Details

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

References

Debusho, L. K., Gemechu, D. B., and Haines, L. M. (2016). Algorithmic construction of optimal block designs for two-colour cDNA microarray experiments using the linear mixed model. Under review.

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

optbdmaeAT