[R] Simulate values
kehld at ktk.pte.hu
Wed Apr 8 04:34:32 CEST 2015
please keep conversation on the list. Your code looks waaaay better now.
I would not name the variable variances2 but that is just a matter of taste.
What you could also do as a one-liner is something like
n <- 40
REPS <- 50000
mu <- 10
sigma <- 5
chisq <- replicate(REPS,(n-1)*var(rnorm(n,mu,sigma))/sigma^2)
Try to draw a histogram of the variances2 or chisq values and superimpose the theoratical distribution.
?hist and ?curve might help.
Feladó: "Mike Brechbühler" [osiris94 at gmx.ch]
Küldve: 2015. április 8. 0:28
To: Kehl Dániel
Tárgy: Aw: RE: [R] Simulate values
Thanks for your answer.
I changed my commands and ended up with:
matrix <- matrix(rnorm(500 * 40, 10, 5), ncol = 40, nrow = 500)
variances1 <- apply(matrix, 1, var)
variances2 <-(40 - 1) * variances1 / 25
What do you think about it? Does that work and was more or less what you expected to see?
Gesendet: Dienstag, 07. April 2015 um 05:39 Uhr
Von: "Kehl Dániel" <kehld at ktk.pte.hu>
An: Osiris10101 <osiris94 at gmx.ch>, "r-help at r-project.org" <r-help at r-project.org>
Betreff: RE: [R] Simulate values
People do not usually do homework stuff here but I do not see the point in repeating the same sample 500 times. You might want to simulate 40x500 independent samples and put those in a matrix (see ?matrix) with lets say 40 rows and 500 columns. Once done, you can apply calculate the 500 sample standard deviations (or the chi-square values) where the ?apply function might help you.
Lets start with that and lets see where you get.
Feladó: R-help [r-help-bounces at r-project.org] ; meghatalmazó: Osiris10101 [osiris94 at gmx.ch]
Küldve: 2015. április 7. 0:52
To: r-help at r-project.org
Tárgy: [R] Simulate values
I'm facing the following task:
Simulate 500 values of the statistic (n-1)s^2/sigma^2 based on taking 500
samples of size n=40
from the N(mu=10; sigma^2 = 25) distribution.
I think with the following command:
I was able to simulate the samples but how I now can simulate the values of
the chi-square-distribution is a mystery to me...
I hope anyone can help me, shouldn't be a big problem...
Thanks in advance!
Reason for posting:
I started a course at the University of Manchester and had to catch up with
R, which I never used back in Switzerland. Now I'm solving some exercises to
get more practice and this is one of them.
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