Perhaps: sim <- apply(x, 1, function(.x)rnorm(1000, .x[2], rnorm(1000,mean= 9.454398,sd=1.980136)))
On 08/02/2008, Steven Van Wilgenburg <[EMAIL PROTECTED]> wrote: > Hello, > > > I wish to examine the influence of error in variables on my analyses > via error propagation. I have a data frame (x) as follows: > > id response > 1 -121 > 2 -131 > 3 -125 > etc..... > > I wish to propagate errors for each row in the data frame, where error > is distributed around the value of the response variable. To do this, I > wish to simulate 1000 variables for each row in the above data frame. I > wrote the following, but suspect that it is not applying the function > to each row.... > > sim<-rnorm(1000,mean=x$response, sd= (rnorm(1000,mean= 9.454398, > sd=1.980136))) > > Do I need to use tapply to have the function iteratively go through > each row? > > Any advice would be appreciated. > > > -Steve > > ______________________________________________ > R-help@r-project.org 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. > -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40" S 49° 16' 22" O ______________________________________________ R-help@r-project.org 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.
