I am looking for a method to generate random numbers using multiple seed sequences.

For example, consider the situation where you are doing some simulation study.

You repeat the following:

analysis 1

1 set seed.

2 generate a traning data set by resampling.

3 analyze the data set by method A.

4 accumulate the result.

5 repeat above 2 to 4.

Now, suppose method A does not use randon munbers in it but

method B uses sone random numbers in it.

Then, the data set generated above may be different from the ones

from below:

analysis 2

1 set seed.

2 generate a traning data set by resampling.

3 analyze the data set by method B (with or withoug setting seed).

4 accumulate the result.

5 repeat above 2 to 4.

Since in order to compare the method, we need to analyse the same data set

generated at the step 2 of the above analyses, we must use two random number

sequences in analysis 2: one with the original seed and one with another in method B.

Or I need to resume the original sequence after another sequence was invoked.

I came up with a method which enables above by modifying .Random.seed in the global envionment, but R help says it is not desirable to modify it.

Can anyone help me to do this.

```
#
# the code starts here.
#
testRN0 <- function( seed, restore=0 ){
# analysis by method A
set.seed(1701)
RNA=matrix(0,2,15)
for( rep in 1:2 ){
# sample osb id
rn=sample(0:9,15, replace=TRUE)
RNA[rep,]=rn
#
# analyze rs1 by method A and accumulate here.
#
} # end of rep lool
# analysis by method B
set.seed(1701)
RNB=matrix(0,2,15)
for( rep in 1:2 ){
# sample osb id
rn=sample(0:9,15, replace=TRUE)
RNB[rep,]=rn
# save the random numbse seed
.R.s=.Random.seed
#
# analyze rs1 by method B and accumulate here.
#
set.seed( 1234 )
temp=sample( 0:9,10)
if( restore ){
# restore random numbse seed
.Random.seed <<- .R.s
}
} # end of rep lool
print(RNA)
print(RNB)
} # end of testRN0
testRN0( 1701 )
testRN0( 1701, restore=1 )
#
# end of code
#
```