test-sim-Aa-optimal-known-var.r
In RARtrials: Response-Adaptive Randomization in Clinical Trials

set.seed(12345)

sim1<-lapply(1:1000,function(x) {sim_Aa_optimal_known_var(Pats=10,nMax=50000,TimeToOutcome=0,
enrollrate=0.9,N2=880,armn=2,mean=c(9.1/100,8.47/100),sd=c(0.009,0.009),alphaa=0.025,side='lower',armlabel =c(1,2))})
sim11<-do.call(rbind,lapply(1:1000,function(x) {sim1[[x]][[3]]}))
vector11<-table(sim11[,4])/880000#allocation ratio should be around 0.5 #0.4998784 0.5001216
all.equal(as.vector(vector11), c(0.5,0.5),tolerance=1e-3)

set.seed(123451)
sim2<-lapply(1:1000,function(x) {sim_Aa_optimal_known_var(Pats=10,nMax=50000,TimeToOutcome=0,
enrollrate=0.9,N2=500,armn=3,mean=c(9.1/100,8.47/100,8.8/100),sd=c(0.009,0.01,0.007),alphaa=0.025,side='lower',armlabel =c(1,2,3))})
sim22<-do.call(rbind,lapply(1:1000,function(x) {sim2[[x]][[3]]}))
vector21<-table(sim22[,4])/500000#allocation ratio should be around  0.428147, 0.3363841, 0.2354689#0.42765 0.33620 0.23615
all.equal(as.vector(vector21), c(0.428147, 0.3363841, 0.2354689),tolerance=1e-2)

set.seed(123452)
sim3<-lapply(1:1000,function(x) {sim_Aa_optimal_known_var(Pats=10,nMax=50000,TimeToOutcome=expression(rnorm( length( vStartTime ),30, 3)),
enrollrate=0.5,N2=400,armn=4,mean=c(9.1/100,8.47/100,8.8/100,8.6/100),sd=c(0.009,0.01,0.007,0.008),alphaa=0.025,side='upper',armlabel =c(1,2,3,4))})
sim33<-do.call(rbind,lapply(1:1000,function(x) {sim3[[x]][[3]]}))
vector31<-table(sim33[,4])/400000#allocation ratio should be around  0.3840613, 0.2463755, 0.1724628, 0.1971004#0.3842975 0.2460250 0.1726475 0.1970300
all.equal(as.vector(vector31), c(0.3840613, 0.2463755, 0.1724628, 0.1971004),tolerance=1e-3)

set.seed(123453)
sim4<-lapply(1:1000,function(x) {sim_Aa_optimal_known_var(Pats=10,nMax=50000,TimeToOutcome=expression(rnorm( length( vStartTime ),30, 3)),
enrollrate=0.5,N2=400,armn=5,mean=c(9.1/100,8.47/100,8.8/100,8.6/100,8.8/100),sd=c(0.009,0.01,0.007,0.008,0.01),alphaa=0.025,side='upper',armlabel =c(1,2,3,4,5))})
sim44<-do.call(rbind,lapply(1:1000,function(x) {sim4[[x]][[3]]}))
vector41<-table(sim44[,4])/400000#allocation ratio should be around  0.3396226415, 0.1886792, 0.13207547, 0.150943396, 0.188679#0.3399050 0.1890125 0.1324775 0.1510225 0.1875825
all.equal(as.vector(vector41), c(0.3396226415, 0.1886792, 0.13207547, 0.150943396, 0.188679),tolerance=1e-2)