[R] trouble double looping to generate data for a meta-analysis

[Bert Gunter]

Hint: It's much more efficient not to loop and generate random data in
a single call only once -- then make your samples. (This can even
often be done with different distribution parameters, as in many cases
these can also be vactorized)

Example:

## 1000 random samples of size 100

> set.seed(1122)
> samps.norm <- matrix(rnorm(1e5),nrow = 100 )
> dim(samps.norm)
[1]  100 1000

## This was instantaneous on my machine.

Cheers,
Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Fri, Jul 1, 2016 at 10:28 AM, Marietta Suarez <marietta0423 at gmail.com> wrote:
> i'm trying to generate data for a meta analysis. 1- generate data following
> a normal distribution, 2- generate data following a skewed distribution, 3-
> generate data following a logistic distribution. i need to loop this
> because the # of studies in each meta will be either 10 or 15. k or total
> number of studies in the meta will be 5. i need to loop twice to repeat
> this process 10 times. database should be 3 columns (distributions) by 65
> rows x 10 reps
>
>
> here's my code, not sure what's not working:
> library(fGarch)
>
> #n reps =10
> rep=10
>
> #begin function here, need to vary n and k, when k=2 n=10, when k3 n=15
> fun=function(n, k){
>
>   #prepare to store data
>   data=matrix(0,nrow=10*k, ncol=3)
>   db=matrix(0,nrow=650, ncol=3)
>
>   for (j in 1:rep)
>   {
>     for (i in 1:k)
>     {
>       #generate data under normal, skewed, and logistic distributions here
>
>       data[,1]=rnorm(n, 100, 15)
>       data[,2]=rsnorm(n, 100, 15, 1)
>       data[,3]=rlogis(n, 100, 15)
>     }
>       [j]=db
>   }
> }
>
> save=fun(10,2)
>
> Please help!!!
>
>         [[alternative HTML version deleted]]
>
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