# cmatbd

0th

Percentile

##### Computes the treatment information matrix

The function cmatbd 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 block design of size 2.

Keywords
information matrix, C-matrix
##### Usage
cmatbd(trt.N, blk.N, theta, des)
##### Arguments
trt.N

integer, specifying number of treatments, v.

blk.N

integer, specifying number of blocks, b.

theta

numeric, representing function of the ratio of random block variance and random error variance. It takes any value between 0 and 1, inclusive.

des

matrix, a 2 x b block design with b blocks of size k = 2 and v treatments.

##### Value

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

##### 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.

Boptbd, fixparBbd, intcbd

• cmatbd
##### Examples
# NOT RUN {
##Information matrix

trt.N <- 3

blk.N <- 3

theta <- 0.2

des <- intcbd(trt.N = 4, blk.N = 3)

cmatbd(trt.N, blk.N, theta, des)
# }

Documentation reproduced from package Boptbd, version 1.0.5, License: GPL-2

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