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optrcdmaeAT (version 1.0.0)

optrcdmaeAT-internal:

Description

Functions for internal usage only.

Usage

## Computes A-optimal or near-optimal row-column designs
## using array exchange algorithm
Aoptrcd.maeA(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes A-optimal or near-optimal row-column designs
## using treatment exchange algorithm
Aoptrcd.maeT(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes MV-optimal or near-optimal row-column designs
## using array exchange algorithm
MVoptrcd.maeA(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes MV-optimal or near-optimal row-column designs
## using treatment exchange algorithm
MVoptrcd.maeT(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes D-optimal or near-optimal row-column designs
## using array exchange algorithm
Doptrcd.maeA(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes D-optimal or near-optimal row-column designs
## using treatment exchange algorithm
Doptrcd.maeT(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes E-optimal or near-optimal row-column designs
## using array exchange algorithm
Eoptrcd.maeA(trt.N, col.N, theta, nrep, itr.cvrgval)
 
## Computes E-optimal or near-optimal row-column designs
## using treatment exchange algorithm
Eoptrcd.maeT(trt.N, col.N, theta, nrep, itr.cvrgval)

Arguments

trt.N
integer, specifying number of treatments, v.
col.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 optrcdmaeAT documentation for details.

Details

These functions are handled via a generic function optrcdmaeAT. Please refer to the optrcdmaeAT 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. Gemechu, D. B., Debusho, L. K., and Haines, L. M. (2015). A-and D-optional row-column designs for two-colour cDNA microarray experiments using linear mixed effects models. South African Statistical Journal, 49, 153-168.

See Also

optrcdmaeAT