cmatrcd.mae: Computes the treatment information matrix

In optrcdmaeAT: Optimal Row-Column Designs for Two-Colour cDNA Microarray Experiments

Description

Computes the information matrix (C-matrix) for treatment effects under either the linear fixed effects model or the linear mixed effects model setting for a given row-column design.

Usage

cmatrcd.mae(trt.N, col.N, theta, des)

Arguments

trt.N	integer, specifying number of treatments, v.
col.N	integer, specifying number of arrays (columns), 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.
des	matrix, a 2 x b row-column design with b arrays/columns of size k = 2 and v treatments.

Value

Returns a v x v treatment information matrix (C-matrix).

Author(s)

Legesse Kassa Debusho, Dibaba Bayisa Gemechu, 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. (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, fixparrcd.mae, intcrcd.mae

Examples

##Information matrix

     trt.N <- 3 
     col.N <- 3 
     theta <- 0.1 
     rcdes <- intcrcd.mae(trt.N = 3, col.N = 3)

     cmatrcd.mae(trt.N = 3, col.N = 3, theta = 0.1, des = rcdes)

optrcdmaeAT documentation built on May 1, 2019, 7:56 p.m.