Matthias Kohl was so kind and provided me the following lines in this issue:
library(distrEx)
chf <- function(t, D){
E(D, function(x){exp(1i*t*x)}, useApply = FALSE)
}
## Normalverteilung
D <- Norm()
t <- seq(-3, 3, by = 0.05)
chf.norm <- sapply(t, chf, D = D)
chf.exakt <- exp(-t^2/2)
chf.diff
Thank you Prof Ripley for your answer.
> > The characteristic function is the inverse Fourier transform of the
> > distribution function. The characteristic function of a normaly
> > distributed random variable is exp(-t^2/2).
> >
>
> The fft is a discrete Fourier transforn, not a continuous one.
On Wed, 30 Apr 2008, Thomas Steiner wrote:
The characteristic function is the inverse Fourier transform of the
distribution function. The characteristic function of a normaly
distributed random variable is exp(-t^2/2).
The fft is a discrete Fourier transforn, not a continuous one.
Further in e
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