soptdmaeA-internal {soptdmaeA}

Internal functions

Description

Functions for internal usage only.

Usage

 
## Computes A-optimal or near-optimal block or row-column designs
## using array exchange algorithm
seqAoptbrcd.maeA(trt.N, blk.N, theta, nrep, strt, sary, des0, dtype)
 
## Computes MV-optimal or near-optimal block or row-column designs
## using array exchange algorithm
seqMVoptbrcd.maeA(trt.N, blk.N, theta, nrep, strt, sary, des0, dtype)
 
## Computes A-optimal or near-optimal block or row-column designs
## using array exchange algorithm
seqDoptbrcd.maeA(trt.N, blk.N, theta, nrep, strt, sary, des0, dtype)
 
## Computes A-optimal or near-optimal block or row-column designs
## using array exchange algorithm
seqEoptbrcd.maeA(trt.N, blk.N, theta, nrep, strt, sary, des0, dtype)


 

Arguments

trt.N

integer, specifying number of treatments v of initial design, des0.

blk.N

integer, specifying number of arrays b of initial design, des0.

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.

strt

a non-negative integer, specifying number of added treatments/conditions to the initial design.

sary

a non-negative integer, specifying number of added arrays to the initial design.

des0

matrix, a 2 x blk.N or blk.N x 2 initial block or row-column design. The initial design must be treatment connected and the number of treatments and arrays should also coincides with trt.N and blk.N inserted by the user, if this conditions are not satisfied, the package will stop running with an error message.

dtype

character, specifying the design type. For block designs, dtype = "blkd" and for row-column deigns, dtype = "rcd".

Details

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

Author(s)

Dibaba Bayisa Gemechu, Legesse Kassa Debusho, and Linda Haines

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

soptdmaeA