Le 18/03/13 16:24, To . . a écrit :
x.1-rnorm(6000, 2.4, 0.6)x.2-rlnorm(1, 1.3,0.1)X-c(x.1, x.2)
hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2,
lwd=2)lines(density(x.2), lty=2, lwd=2)lines(density(X), lty=4)
Here is a solution:
x.1-rnorm(6000, 2.4, 0.6)
x.2-rlnorm(1,
Hello
I am trying to find an automated way of fitting a mixture of normal and
log-normal distributions to data which is clearly bimodal.
Here's a simulated example:
x.1-rnorm(6000, 2.4, 0.6)x.2-rlnorm(1, 1.3,0.1)X-c(x.1, x.2)
hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2,
Hello
I am trying to find an automated way of fitting a mixture of normal and
log-normal distributions to data which is clearly bimodal.
Here's a simulated example:
x.1-rnorm(6000, 2.4, 0.6)
x.2-rlnorm(1, 1.3,0.1)
X-c(x.1, x.2)
hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2,
You posted this earlier. Do not repost, please. It was seen.
-- Bert
On Mon, Mar 18, 2013 at 3:28 PM, To . . kid...@hotmail.com wrote:
Hello
I am trying to find an automated way of fitting a mixture of normal and
log-normal distributions to data which is clearly bimodal.
Here's a
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