| aoptbbpb {Aoptbdtvc} | R Documentation |
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)Arguments
v1 |
number of test treatments |
v2 |
number of controls |
b |
number of blocks |
k |
block size |
ntrial |
number of trials, default is 5 |
Value
It either returns a text message 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 |
Note
The function is useful to construct A-optimal BBPB designs for v1+v2 <= 30 and up to block size 10. May not be very useful beyond v1+v2 > 30. For k<=3, designs with larger v1+v2 may be obtained.
Author(s)
Baidya Nath Mandal <mandal.stat@gmail.com>
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
## Not run: aoptbbpb(3,3,12,4)