How to generate a matrix of Beta or Binomial distribution

Hi Rui,

Many thanks for your excellent code! That works very well. But I still 
have a kind of naive question about the set.seed(1)

Consider shape1=c(1,3) and shape2=c(2,4)

Using R I got that

set.seed(1)
rbeta(2,c(1,3),c(2,4))

[1] 0.5803922 0.4679171

set.seed(1)
c(rbeta(1,1,2),rbeta(1,3,4))

[1] 0.5803922 0.4679171

They have the same outputs. So rbeta(2,shape1,shape2) is the correct 
solution which is equivalent to operating rbeta() componentwise to 
shape1 and shape2. This is exactly the solution I wanted. Thanks a lot!

But I also found the following:

set.seed(1)

rbeta(1,1,2)

[1] 0.5803922

set.seed(1)
rbeta(1,3,4)

[1] 0.3016368

This is pretty strange. Why is the second one 0.3016368 instead of 
being 0.4679171? Probably I was wrong somewhere here.

The binomial code works very well. Thanks for this very much!

Have a nice day.
Jeff

? 8/27/2012 1:25 PM, Rui Barradas ??:

Hello,

Try the following.

set.seed(1)
X <- rbeta(2*length(shape1), rep(shape1, each = 2), rep(shape2, each 
= 2))
X <- matrix(X, ncol = 2, byrow = TRUE)

#-- binomial

n <- 10
p <- runif(10000)

Y1 <- matrix(nrow = 10000, ncol = 10)

set.seed(6292)
for(i in 1:10000){
      Y1[i, ] <- rbinom(n, 2, p[i])
}

set.seed(6292)
Y2 <- rbinom(n*length(p), 2, rep(p, each = 10))
Y2 <- matrix(Y2, ncol = n, byrow = TRUE)

identical(Y1, Y2) #TRUE

The trick is not to use argument recycling.

Hope this helps,

Rui Barradas

Em 27-08-2012 15:49, JeffND escreveu:

Hi folks,

I have a question about how to efficiently produce random numbers 
from Beta
and Binomial distributions.

For Beta distribution, suppose we have two shape vectors shape1 and 
shape2.
I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from
reta(2,shape1[i]mshape2[i]). Of course this can be done via loops:

for(i in 1:10000)
{
X[i,]=rbeta(2,shape1[i],shape2[i])
}

However, the above code is time consuming. It would be better to 
directly
generate X without any loops. I tried the following code

X<- rbeta(2,shape1,shape2)

but it looks not right. So I was wondering if there is an R code 
doing this.

For Binomial distribution, I have a similar question.  I hope to 
generate a
10000 x n matrix Y whose i th row is a sample from rbinom(n,2,p[i]), 
where p
is a vector of binomial probabilities. We can also do it by loops

for(i in 1:10000)
{
Y[i,]=rbinom(n,2,p[i])
}

But it would be nice to do it without using any loops. Is this 
possible in
R?

Many thanks for great help and suggestions!
Jeff









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