From: Petr Klasterecky <klaster_at_karlin.mff.cuni.cz>

Date: Wed 04 Apr 2007 - 05:53:25 GMT

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

[10,] 1.4814704 3.3024049 4.194628

[10,] 1.4814704 3.3024049 4.194628

Date: Wed 04 Apr 2007 - 05:53:25 GMT

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 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Wed Apr 04 15:57:49 2007

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