I want to simulate the end point of a one-dimensional brownian motion going on for many timesteps (n very large). Can this be done more efficiently than (effect of drift excluded): endpoint <- sum(rnorm(n)) Thanks in advance! Karsten -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
sum(rnorm(n)), calculate more efficiently
2 messages · Karsten D Bjerre, Deepayan Sarkar
On Wednesday 20 November 2002 09:58 am, Karsten D Bjerre wrote:
I want to simulate the end point of a one-dimensional brownian motion going on for many timesteps (n very large). Can this be done more efficiently than (effect of drift excluded): endpoint <- sum(rnorm(n))
Do you really mean a one-dimensional random walk ? The sum of n independent N(0,1) variables is N(0, n), so if you are interested in only the endpoint, you might as well use that fact. Deepayan -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._