Not sure whether this is exactly and everything you want, but at least 
it may give you some ideas how to proceed. You do not need loops at all:

Let's try a simplified example with 3 samples, each of length 10 (just 
for printing purposes):

m <- c(1,2,3)
v <- c(1,4,9)
n <- 10
means <- rep(m,each=n)
vars <- rep(v,each=n)
means
  [1] 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3
vars
  [1] 1 1 1 1 1 1 1 1 1 1 4 4 4 4 4 4 4 4 4 4 9 9 9 9 9 9 9 9 9 9

numbers <- matrix(rnorm(length(means), mean=means, sd=sqrt(vars)), 
nrow=n, byrow=F)
numbers
             [,1]       [,2]      [,3]
  [1,]  0.9721407  0.4510903 -2.880967
  [2,] -0.4834124 -2.7958993 -1.368037
  [3,]  1.6871736 -0.6717009 -3.268698
  [4,]  0.9738312  3.1919293  3.982135
  [5,]  0.8032162  1.0397078  7.227974
  [6,] -0.1606657  2.6339503  5.873210
  [7,]  0.5786295 -0.3589869  4.194425
  [8,]  0.9909184  2.0622899  6.432129
  [9,]  3.1687842  1.9765014  3.788201
[10,]  1.4814704  3.3024049  4.194628

colnames(numbers) <- paste('Ux',1:length(m),sep='')
numbers
              Ux1        Ux2       Ux3
  [1,]  0.9721407  0.4510903 -2.880967
  [2,] -0.4834124 -2.7958993 -1.368037
  [3,]  1.6871736 -0.6717009 -3.268698
  [4,]  0.9738312  3.1919293  3.982135
  [5,]  0.8032162  1.0397078  7.227974
  [6,] -0.1606657  2.6339503  5.873210
  [7,]  0.5786295 -0.3589869  4.194425
  [8,]  0.9909184  2.0622899  6.432129
  [9,]  3.1687842  1.9765014  3.788201
[10,]  1.4814704  3.3024049  4.194628

Now your random vectors are in columns of 'numbers' and you can work 
with them using indexing.

Petr

projection83 napsal(a):
> I am used to java (well, i dont remember it really well, but anyway)
> 
> I have having a really difficult time making simple loops to work. I got the
> following to work:
> 
>          ##
>       ##Creates objects Ux1, Ux2, Ux2 etc. that  all contain n numbers in a
> random distribution
>       ##
>       m<-c(m1,m2,m3,m4,m5,m6,m7,m8,m9,m10)#these are defined as numbers 
> (means)
>       v<-c(v1,v2,v3,v4,v5,v6,v7,v8,v9,v10)#these are defined as numbers
> (variances)      
>         n<-50
>       for(k in 1:g)
>       {
>               assign( paste("Ux", k, sep=""), rnorm( n  , 
> assign(paste("m",1,sep=""),m[k])   ,   assign(paste("m",1,sep=""),v[k])  )  
> )
>       }
> 
> 
> The above seems like a lot of work for such a simple feat, no?
> 
> Also, I CANNot get the following to work in a loop manor:
> 
>         Ux1i<-as.integer(Ux1)
>       Ux2i<-as.integer(Ux2)
>       Ux3i<-as.integer(Ux3)
> 
> or
> 
>       Sx1<-sort(Ux1i)
>       Sx2<-sort(Ux2i)
>       Sx3<-sort(Ux3i)
> 
> Maybe I am just not using matrixes enough? but even that seems quite a lot
> more complex than calling x<-matrix() then grabbing values by
> x[j][k]...(java style if i remember correctly). the matrix help in R dosnt
> make much sense to me. And also i am not sure why numeric() dosnt make you
> define length before you use it, yet matrix() does.  Is there some other
> funciton that i should be using to make length not an issue?
> 
> 
> All in all, I dont know if i am going about this loop stuff a reaaaaly round
> about way - Any help would make me much less loopy:Pthanks 
> 
> 
> 

-- 
Petr Klasterecky
Dept. of Probability and Statistics
Charles University in Prague
Czech Republic

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