Edit Question - KnowledgeHub

Title Body

R ignores setting .Random.seed inside of an lapply. Using set.seed however, works fine. Some code: # I can save the state of the RNG for a few seeds seed.list <- lapply( 1:5, function(x) { set.seed(x) seed.state <- .Random.seed print( rnorm(1) ) return( seed.state )}) #[1] -0.6264538 #[1] -0.8969145 #[1] -0.9619334 # But I get different numbers if I try to restore # the state of the RNG inside of an lapply tmp.rest.state <- lapply(1:5, function(x) { .Random.seed <- seed.list[[x]] print(rnorm(1))}) # [1] -0.2925257 # [1] 0.2587882 # [1] -1.152132 # lapply is just ignoring the assignment of .Random.seed .Random.seed <- seed.list[[3]] print( rnorm(1) ) # The last printed value from seed.list # [1] -0.9619334 print( rnorm(1) ) # The first value in tmp.rest.state # [1] -0.2925257 My goal is to checkpoint MCMC runs so that they can be resumed exactly. I can easily save the state of the RNG, I just can't get R to load it inside of an lapply loop! Is there a way to force R to notice setting .Random.seed ? Or is there a simpler way to make this happen? In case it matters, I'm using 64 bit R: R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows" Platform: x86_64-pc-linux-gnu (64-bit) On Ubuntu 12.04 LTS: nathanvan@nathanvan-N61Jq:~$ uname -a Linux nathanvan-N61Jq 3.2.0-26-generic #41-Ubuntu SMP Thu Jun 14 17:49:24 UTC 2012 x86_64 x86_64 x86_64 GNU/Linux

Tags (comma-separated) Cancel