Hi,
my first guess is that the algorithm returns a negative value in some
step - recall that you start from 0.0207!! This negative value is then
passed as standard error to qnorm and that cannot work...
My guess is based on a small experiment where I tried a different
starting point (.02 is so close to 0 that one cannot see anything):
xsd <- optim(20, fr, NULL,method="BFGS",control=list(trace=6))
The warnings which you didn't include also tell you about NaNs in
qnorm() - another strong indication of wrong arguments to qnorm().
Try constrained optimization to resctrict to positive values.
See ?constrOptim or use optim() with a method allowing for box
constraints - see ?optim, arguments lower, upper.
Petr
livia napsal(a):
> Hi, I would like to minimize the value of x1-x2, x2 is a fixed value of 0.01,
> x1 is the quantile of normal distribution (0.0032,x) with probability of
> 0.7, and the changing value should be x. Initial value for x is 0.0207. I am
> using the following codes, but it does not work.
>
> fr <- function(x) {
> x1<-qnorm(0.7,0.0032,x)
> x2=0.01
> x1-x2
> }
> xsd <- optim(0.0207, fr, NULL,method="BFGS")
>
> It is the first time I am trying to use optimization. Could anyone give me
> some advice?
--
Petr Klasterecky
Dept. of Probability and Statistics
Charles University in Prague
Czech Republic
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