UniDOE (version 1.0)

AUDC: Augmented Uniform Design Construction

Description

This function takes n,s,q; a unchanged initial design and other arguments to output a list(described below).

Usage

AUDC(X0,n,crit,maxiter,hits_ratio,vis)

Arguments

X0

an integer matrix R object

n

an integer R object. Run of Experiment

crit

an character R object. Type of criterion to use.

"maximin" -- maximin Discrepancy ;

"CL2" --Centered L2 Discrepancy ;

"MD2" --Mixture L2 Discrepancy ;

maxiter

a positive integer R object. Maximum iteration number in outer while loop of SOAT algorithm.

hits_ratio

an float R object. Default value is 0.1, which is the ratio to accept changes of design in inner for loop. Details can be checked in (Zhang, A. and Li, H. (2017). UniDOE: an R package for uniform design construction via stochastic optimization.)

vis

an boolean R object. If true, plot the criterion value sequence.

Value

A list that contains Initial design matrix(initial_design),optimal design matrix(final_design), initial criterion value(initial_criterion), final criterion value(criterion_value) and criterion list(criterion_lists) in update process.

References

Zhang, A. and Li, H. (2017). UniDOE: An R package for constructing uniform design of experiments via stochastic and adaptive threshold accepting algorithm. Technical Report.

Examples

# NOT RUN {
#e.g.1.
#Set a fixed initial matrix:
n=12#(must be multiples of q)
mat0 = matrix(c(1,1,1,2,2,2,3,3,3),ncol=3,byrow=TRUE)# nb. of columns=s
crit = "MD2"#(Mixture L2 criteria)
list1=AUDC(X0=mat0,n,crit=crit,maxiter=100)

#e.g.2.
#Set a fixed initial matrix with visualization:
n=9#(must be multiples of q)
mat0 = matrix(c(1,1,1,2,2,2,3,3,3),ncol=3,byrow=TRUE)# nb. of columns=s
crit = "MD2"#(Mixture L2 criteria)
vis= TRUE
list1=AUDC(X0=mat0,n,crit=crit,vis=vis,maxiter=100)

# }