Kervahu Anne wrote:
> Hi,
>
> I try to fit a non linear regression by minimising the sum of the sum of
> squares.
>
> The model is number[2]-(x/number[1])^number[3]
> Number [2] and number [1] change as the data changes but for all the set of
> data number[3] must be identical.
>
> I have 3 set of data (x1,y1), (x2,y2), (x3,y3).
>
> x_a<-c(0,0.5,1,1.5,2,3,4,6)
> y_a<-c(5.4,5,4.84,4.3,4,2,1.56,1.3)
>
> x_b<-c(0,1,2,3,4,5,6,7,8,9,10,11,12)
> y_b<-c(5.34,4.98,4.66,4.06,3,3.4,2.7,2.9,2.6,2.6,1.9,1.3,1.4)
>
> x_c<-c(0,3,6,8,10,12,14,16,18,20,24,26,28,30)
> y_c<-c(5.5,5.1,4.3,4,3.7,3.2,3.04,2.778,2.56,2.25,1.78,1.44,1.32,1.2)
>
> x<-c(x_a,x_b,x_c)
> y<-c(y_a,y_b,y_c)
> long<-c(0,8,21,35)
>
> Hence, the sum of squares is:
>
> Sce= sum( sum((y- number[4]-(x/number[1])^number[7])^2)+
> sum((y- number[5]-(x/number[2])^number[7])^2)+
> sum((y- number[6]-(x/number[3])^number[7])^2)+
>
> for minimising this sum, I compute the function "sce":
>
> sce<-function(param){
> sce_yest<-matrix(nrow=3,ncol=1)
> for( i in 1:3){
> yy<-(y[((long[i]+1):long[i+1])])
> xx<-x[(long[i]+1):(long[i+1])]
> y_est<-(param[i+2]-(xx/param[i])^param[(2*3)+1])
> sce_yest[i,]<-sum((yy-y_est)^2)
> }
> return(sum(sce_yest))
> }
>
> Then, I use the fonction optim for obtaining a vector of 7 parameters which
> will minimise the fonction sce. I use initial parameters at random that I
> don't have a answer relating to a minimum local.
>
> pinit=c(runif(3,min=0,max=10), runif(3,min=3,max=8),runif(1,min=0,max=4))
> optim(p=pinit,sce)
>
> if I use the function as above, I got an answer but the value of the
> parameters is not in the interval I want. So I applied
>
> optim(p=pinit,sce, method="L-BFGS-B", lower=c(0,0,0,0,0,0,0),
upper=c(10,
> 10,10,10,10,10,4),control=list(maxit=20000000,temp=20000))
>
> but the program does not run. And I get this message
>
> "Error in optim(p = pinit, sce, method = "L-BFGS-B", lower =
pinf, upper > psup, :
> L-BFGS-B needs finite values of fn"
As it says, you get infinite values, probably from
(x/number[1]) ...
Uwe Ligges
>
> And I don't understand why it doesn't work. Do I forget an option
in optim
> computation. Or is there an other function instead of optim that I can use.
>
> Thanks in advance
>
> Anne Kervahu
> annekervahu at yahoo.fr
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html