GenAUD {UniDOE} | R Documentation |
This function takes n,s,q; a unchanged initial design and other arguments to output a list (described below).
GenAUD(X0,n,crit,maxiter,hits_ratio,vis)
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; "CD2" –Centered L2 Discrepancy; "WD2" – Wrap-around 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 constructing uniform design of experiments via stochastic and adaptive threshold accepting algorithm. Technical Report.) |
vis |
an boolean variable. If true, plot the trace of criterion values. |
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.
Aijun Zhang, Haoyu Li, Shijie Quan
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.
#Example 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) res = GenAUD(X0=mat0,n,crit=crit,maxiter=100) # Example 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) crit = "MD2" #(Mixture L2 criteria) list1=GenAUD(X0=mat0,n,crit=crit,vis=TRUE,maxiter=100)