I'm having an issue with a for loop and the runif() function. My goal is to determine a regression line out of two Uniform Distributions U(0,2). The thing is I'm using a for loop to simulate several quantities out of the runif and then calculate the regression line. For instance, 10 simulations from 100:1000 with an increment of 100 each time. So that gives me some values
set.seed(69420)
#Vr<-matrix(data= ,nrow =10, ncol=2)
i<-0
for(j in 1:10){
for(i in x){
i<-i+100
J<-runif(i , min=0 , max=2)
M<-runif(i , min=0 , max=2)
L<-pmax(J,M)#assign time to loser
W<-pmin(J,M)#assign time to winner
mW<-mean(W)
mL<-mean(L)
plot(W,L,xlim=c(0,2),ylim=c(0,2))
abline(v=0,col='salmon')
abline(h=0,col='steelblue')
vW<-mean((W-mean(W))^2)
vL<-mean((L-mean(L))^2)
cWL<-mean((L-mean(L))*(W-mean(W)))
a=cWL/vW
b=mean(L) - (cWL*mean(W))/vW
#Vr[j,1]<-c(a)
#Vr[j,2]<-c(b)
abline(b,a,lwd=2, col="gray60")
}
[1,] 0.3649283 1.1337290
[2,] 0.4455959 1.0407265
[3,] 0.5418103 0.9433790
[4,] 0.4919243 1.0179350
[5,] 0.5271277 0.9813729
[6,] 0.5328144 0.9743172
[7,] 0.5095540 0.9860148
[8,] 0.5022895 0.9942346
[9,] 0.5663103 0.9276580
[10,] 0.5258270 0.9848213
But if then I take out the for loop and set the numbers of observations 'manually', the outcome for a and b is different from the one with the loop. i=1000
set.seed(69420)
#Vr<-matrix(data= ,nrow =10, ncol=2)
i<-0
J<-runif(1000 , min=0 , max=2)
M<-runif(1000 , min=0 , max=2)
L<-pmax(J,M)#assign time to loser
W<-pmin(J,M)#assign time to winner
mW<-mean(W)
mL<-mean(L)
plot(W,L,xlim=c(0,2),ylim=c(0,2))
abline(v=0,col='salmon')
abline(h=0,col='steelblue')
vW<-mean((W-mean(W))^2)
vL<-mean((L-mean(L))^2)
cWL<-mean((L-mean(L))*(W-mean(W)))
a=cWL/vW
b=mean(L) - (cWL*mean(W))/vW
abline(b,a,lwd=2, col="gray60")
and the result is
[1] 0.4766998 1.010351
which clearly differs from the previous result
Maybe it´s something to do with the set.seed but i dont know. Thank you and any help would be greatly appreciated
I believe this is a scoping issue.... so if you put the set seed within the the loop. Functions are like an environment within the global environment, so I believe if you put the seed within the function it should fix it.
so here:
i<-0
for(j in 1:10){
for(i in x){
set.seed(69420)
i<-i+100
J<-runif(i , min=0 , max=2)
M<-runif(i , min=0 , max=2)