:28
To: Kehl D�niel
T�rgy: Aw: RE: [R] Simulate values
Hey Daniel,
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 thin
Thanks for your final paragraph, we sometimes see people who want us
to do their homework for them and that does not go over well, but I
think you situation is one where many would be happy to help. So here
are some hints to help:
The rnorm command expects the standard deviation, not the variance
7. 0:52
To: r-help@r-project.org
Tárgy: [R] Simulate values
Hello,
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:
rep(rnorm(40,
Hello,
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:
rep(rnorm(40,10,25),times=500)
I was able to simulate the samples but how I now ca
Hello Keith,
see ?Acoef for retrieving the coefficients. Incidentally, in the package dse
simulation methods are made available.
Best,
Bernhard
Dr. Bernhard Pfaff
Director
Global Asset Allocation
Invesco Asset Management Deutschland GmbH
An der Welle 5
D-60322 Frankfurt am Main
Tel: +49 (0)6
Folks,
What is the best way to simulate values from a fitted "VAR {vars}" model.
Also I have tried to use SVAR for a cointegration fit of y~x (just two
univariate time-series) but I can't figure out how to set up the "A" matrix so
that x_t can be used as a contemporaneous predictor of y_t.
Th
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