Fred,
If you want to produce log normal values you can do it by using rlnorm, and you have to provide the mean and variance of the process in log scale, wich means after log transform. Or you can produce them with rnorm and exponentiate.
Check:
> set.seed(1) > rlnorm(100, 0, 1)->vec > set.seed(1) > rnorm(100, 0, 1)->vec2 > all.equal(exp(vec2),vec) [1] TRUE
In both cases I'm using mean=0 and var=1.
Regards
EJ
Frederic renaud wrote:
This values come from R. I 've read the doc but...
If I've understood, I must write
rlnorm(10000,0,0)) to have a mean = 1 and Var =1
but that doesn't work (log 1 =0)
--- Ernesto Jardim <[EMAIL PROTECTED]> wrote:
Where did you get those values ?
> mean(rlnorm(10000,0,1)) [1] 1.667496 > var(rlnorm(10000,0,1)) [1] 4.666731
Look at previous emails, they are more explicit. The
basis is that you must give the mean and variance in log scale.
EJ
Frederic renaud wrote:
yes but mean(rlnorm(10000,0,1)) ne 0 and var(rlnorm(10000,0,1)) ne 1
???
--- Ernesto Jardim <[EMAIL PROTECTED]> wrote:
args(rlnorm)
function (n, meanlog = 0, sdlog = 1) NULL
Frederic renaud wrote:
Hi! I 've a problem to have a lognorm distribution
with
mean=1 and var (or sigma)=1.
rlnorm(1000,0,0) rlnorm(1000,1,1) rlnorm(1000,0,1) .... ?
Can you help me?
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