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1. simulation (score: 1): Author: SMMWORK@aol.com; Date: Sun, 14 Jan 2001 19:42:05 EST; A friend of mine sent me the following message. My inclination is to respond by saying that he needs to set up distribution parameters for a n-variate distribution (i.e. 2 variables --> simulate bi-v; /archives/html/s-news/2001-01/msg00097.html (6,755 bytes)
2. Re: simulation (score: 1): Author: Abdulkadir Hussein <hussein@math.ualberta.ca>; Date: Sun, 14 Jan 2001 21:36:52 -0700 (MST); I am afraid I missed your point. But, if I did not then, you simply need rmvnorm(N, mean=your.mean, cov=your.cov.matrix) For instance (example from S-plus help), generates 5 i.i.d rows of bivariate n; /archives/html/s-news/2001-01/msg00098.html (9,269 bytes)
3. simulation (score: 1): Author: Daikwon Han <dhan@acsu.buffalo.edu>; Date: Thu, 16 Nov 2000 20:00:33 -0500 (EST); Dear all, Can anyone help me to create 100 numbers from the below program ? I'm doing simulation to pick up random numbers and calculate the change of total values over time. The first thing I did is; /archives/html/s-news/2000-11/msg00166.html (7,611 bytes)
4. Re: simulation (score: 1): Author: "Martin H. H. Stevens" <hstevens@rci.rutgers.edu>; Date: Fri, 17 Nov 2000 08:47:14 -0500; There are a zillion ways on this one, but how about: sum.fun <- function(n,cutoff) { a <- runif(n, 0, 1) sum(as.numeric(a < cutoff)) } length <- 100 x <- numeric(length) for( i in 1:length) x[i] <- s; /archives/html/s-news/2000-11/msg00167.html (9,096 bytes)
5. RE: simulation (score: 1): Author: "Buttrey, Samuel" <sebuttre@nps.navy.mil>; Date: Fri, 17 Nov 2000 08:09:02 -0800; You might create a matrix, 100 by n: mat <- matrix (runif (100 * n), nrow = 100) then apply a function to each row to compute the sum of those numbers under .01: apply (mat, 1, function(x) sum (x < .; /archives/html/s-news/2000-11/msg00172.html (9,259 bytes)
6. RE: simulation (score: 1): Author: ASinclair@edfman.co.uk; Date: Fri, 17 Nov 2000 16:17:13 -0000; How about Ntrials <- 100 trials <- sapply(1:Ntrials, function(trialnumber) sum(runif(1000,0,1) < .01) ) This is pretty quick on my machine, about 15 seconds for Ntrials = 10000. The tapply method whi; /archives/html/s-news/2000-11/msg00173.html (10,236 bytes)
7. re:simulation (score: 1): Author: Daikwon Han <dhan@acsu.buffalo.edu>; Date: Sat, 18 Nov 2000 15:39:26 -0500 (EST); Dear all: Thank you so much for all the replys regarding my question of how to generate a matrix from random sampling. I was very excited when I got many responses in a day or so and it worked out !; /archives/html/s-news/2000-11/msg00183.html (7,504 bytes)

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