R help - Nov 2013 - optimization

x1<-c(5.548,4.896,1.964,3.586,3.824,3.111,3.607,3.557,2.989,18.053,3.773,1.253,2.094,2.726,1.758,5.011,2.455,0.913,0.890,2.468,4.168,4.810,34.319,1.531,1.481,2.239,4.204,3.463,1.727)
y<-c(2.590,3.770,1.270,1.445,3.290,0.930,1.600,1.250,3.450,1.096,1.745,1.060,0.890,2.755,1.515,4.770,2.220,0.590,0.530,1.910,4.010,1.745,1.965,2.555,0.770,0.720,1.730,2.860,0.760)
x2<-c(0.137,2.499,0.419,1.699,0.605,0.677,0.159,1.699,0.340,2.899,0.082,0.425,0.444,0.225,0.241,0.099,0.644,0.266,0.351,0.027,0.030,3.400,1.499,0.351,0.082,0.518,0.471,0.036,0.721)
k<-rep(1,29)
x<-data.frame(k,x1,x2)

freg<-function(y,x1,x2){
  reg<- rlm(y ~ x1 + x2 , data=x)
  return(reg)
}


 func <- function(x1,x2,b){
      fit<-freg(y,x1,x2)
        b<-c(coef(fit))
      dv<-1+ b[2]*x2^b[3]
        dv1<-b[2]*x2^b[3]*log(x2)
      out <- ( x1/(1+ b[2]*x2^b[3]))
      out1<-  c(-x1*x2^b[3]/dv^2,-x1* dv1/dv^2)
        return(list( out,out1))
       }>
optim(par=c(b[2],b[3]), fn=out, gr =out1,
        method = c("BFGS"),
        lower = -Inf, upper = Inf,
        control = list(), hessian = T)
can someone help me try running this code because i try many occasion but prove 
abortive. the aim is
to optimize the parameter of the model that is parameter estimates using
optimization

	[[alternative HTML version deleted]]

There are lots of errors in your code. In particular, the optimization
routines do not like functions that ignore the parameters.

And you have not provided out or out1 to the optimizer -- they are
returned as elements of func(), but not correctly.

Please try some of the examples for optim or optimx to learn how to
structure your problem.

JN


On 13-11-16 06:00 AM, r-help-request at r-project.org
wrote:
> Message: 19
> Date: Fri, 15 Nov 2013 09:17:47 -0800 (PST)
> From: IZHAK shabsogh <ishaqbaba at yahoo.com>
> To: "r-help at r-project.org" <r-help at r-project.org>
> Subject: [R] optimization
> Message-ID:
> 	<1384535867.58595.YahooMailNeo at web142506.mail.bf1.yahoo.com>
> Content-Type: text/plain
> 
>
x1<-c(5.548,4.896,1.964,3.586,3.824,3.111,3.607,3.557,2.989,18.053,3.773,1.253,2.094,2.726,1.758,5.011,2.455,0.913,0.890,2.468,4.168,4.810,34.319,1.531,1.481,2.239,4.204,3.463,1.727)
>
y<-c(2.590,3.770,1.270,1.445,3.290,0.930,1.600,1.250,3.450,1.096,1.745,1.060,0.890,2.755,1.515,4.770,2.220,0.590,0.530,1.910,4.010,1.745,1.965,2.555,0.770,0.720,1.730,2.860,0.760)
>
x2<-c(0.137,2.499,0.419,1.699,0.605,0.677,0.159,1.699,0.340,2.899,0.082,0.425,0.444,0.225,0.241,0.099,0.644,0.266,0.351,0.027,0.030,3.400,1.499,0.351,0.082,0.518,0.471,0.036,0.721)
> k<-rep(1,29)
> x<-data.frame(k,x1,x2)
> 
> freg<-function(y,x1,x2){
>   reg<- rlm(y ~ x1 + x2 , data=x)
>   return(reg)
> }
> 
> 
>  func <- function(x1,x2,b){
>       fit<-freg(y,x1,x2)
>         b<-c(coef(fit))
>       dv<-1+ b[2]*x2^b[3]
>         dv1<-b[2]*x2^b[3]*log(x2)
>       out <- ( x1/(1+ b[2]*x2^b[3]))
>       out1<-  c(-x1*x2^b[3]/dv^2,-x1* dv1/dv^2)
>         return(list( out,out1))
>        }>
> optim(par=c(b[2],b[3]), fn=out, gr =out1,
>         method = c("BFGS"),
>         lower = -Inf, upper = Inf,
>         control = list(), hessian = T)
> can someone help me try running this code because i try many occasion but
prove  abortive. the aim is
> to optimize the parameter of the model that is parameter estimates using
optimization
> 
> 	[[alternative HTML version deleted]]