# [R] optimization problem

tedzzx zengzhenxing at gmail.com
Fri Nov 28 08:30:56 CET 2008

```Hi, all

I am facing an optimization problem. I am using the function optim(par,fun),
but I find that every time I give different original guess parameter, I can
get different result. For example
I have a data frame named data:
price     s     x         t
1 1678.0 12817 11200 0.1495902
2 1675.5 12817 11200 0.1495902
3 1678.0 12817 11200 0.1495902
4 1688.0 12817 11200 0.1495902
5 1677.0 12817 11200 0.1495902
6 1678.5 12817 11200 0.1495902
…….
…….
…….

f<-function(p,...){
v=exp(p[1]+p[2]*(x/s)+p[3]*(x/s)^2)
d1=(log(s/x)+(v^2)*t/2)/(v*sqrt(t))
d2=(log(s/x)-(v^2)*t/2)/(v*sqrt(t))
sum((price-(s*pnorm(d1)-x*pnorm(d2)))^2)
}
p=c(-0.1,-0.1,0.01)
optim(par=p,f) # use the default algorism

\$par
[1] -1.2669459  0.4840307 -0.6607008

\$value
[1] 14534.56

\$counts
154       NA

\$convergence
[1] 0

If I try a different original guess estimes, I can get different number
> p=c(-1,-0.1,0.5)
> optim(par=p,f)
\$par
[1] -0.7784273 -0.4776970 -0.1877029

\$value
[1] 14292.19

\$counts
76       NA

\$convergence
[1] 0

\$message
NULL

I have other different original estimes, It also show me different result.

Why?

Thanks.

--
View this message in context: http://www.nabble.com/optimization-problem-tp20730032p20730032.html
Sent from the R help mailing list archive at Nabble.com.

```