Aoptbdtvc (version 0.0.2)

aoptbbpb: A-optimal balanced bipartite block designs

Description

This function generates A-optimal balanced bipartite block (BBPB) designs for tests vs controls comparisons with specified parameters

Usage

aoptbbpb(v1,v2,b,k,ntrial)

Value

It either returns a message that "Design not found" or "BBPB Design does not exist for these parameters" or a design. If a design is found, it returns a list with following components

parameters

parameters of the design

design

generated A-optmal BBPB design

N

incidence matrix of the generated A-optmal BBPB design

NNP

concurrence matrix of the generated design

Aeff

A-efficiency of the design

type

R- type or S- type design

Arguments

v1

number of test treatments

v2

number of controls

b

number of blocks

k

block size

ntrial

number of trials, default is 5

Author

Baidya Nath Mandal <[e-mail]>

References

Jaggi, S., Gupta, V. and Parsad, R. (1996). A-efficient block designs for comparing two disjoint sets of treatments, Communications in Statistics-Theory and Methods 25(5), 967–983.

Mandal, B. N., Parsad, R. and Dash, S. (2017). A-optimal block designs for comparing test treatments with control treatment(s) - an algorithmic approach, upcoming project report, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.

Examples

##construct an A-optimal BBPB design with 5 test treatments and 3 control treatments in 
##12 blocks each of size 5
aoptbbpb(v1=5,v2=3,b=12,k=5)
##construct an A-optimal BBPB design with 6 test treatments and 3 control treatments in 
##6 blocks each of size 8
aoptbbpb(v1=6,v2=3,b=6,k=8)
##Design does not exist
#not run
aoptbbpb(3,2,9,3)
aoptbbpb(6,3,9,4)
#Design not found
if (FALSE) aoptbbpb(3,3,12,4)