search for: matrix_u

...function to do the normal distribution simulation. rm(list=ls()) t <- u<- mann<- rep(0, 45) Nsimulation<-function(S1,S2,Sds,nSims) { set.seed(1) for (sim in 1:nSims) { matrix_t <-matrix(0,nrow=nSims,ncol=3) matrix_u<-matrix(0,nrow=nSims,ncol=3) matrix_mann <-matrix(0,nrow=nSims,ncol=3) #generate random samples from 2 normal distribution x<-rnorm(S1,5,Sds) y<-rnorm(S2,5,4) #extract p-value out and store every p-value into matrix...

...des separately for all of the cases. But i have been told that it can all been done within one code. can anyone give me a brief idea on it. I just managed to write till here and it perhaps isnt correct .. #set up matrix for storing data from simulation matrix_t <-matrix(0,nrow=nSims,ncol=3) matrix_u<-matrix(0,nrow=nSims,ncol=3) matrix_mann <-matrix(0,nrow=nSims,ncol=3) sample_sizes<- matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), nrow=2) p1<-p2<-p3<-vector() nSims<-10 alpha<-0.05 set.seed(1) simulation<-f...