[R] Fitting model with response and day bias

[Bart Joosen]

Hi,

I'm trying to fit a model which has a response bias, but also a day to day 
bias.
If I try to simulate the data, I don't get the right values with optim, and 
also I can't
use the function to give a prediction interval.

My simulated data are:

DF <- as.data.frame(cbind(x=rep(1:10,2),dag=rep(1:2,each=10)))
bias <- c(-0.2,0.5)
DF$y <- ((DF$x-0.1) * 5)+2 + bias[DF$dag]+rnorm(20,0,sd=0.5)


Which I try to fit with:
fn <- function(x){
    a <- x[1]
    b <- x[2]
    c <- x[2]
    sum((DF$y - (((DF$x-c)*a)+b + x[DF$dag+2]))^2)
    }
optim(c(1,1,1,1,1),fn)

But with poor succes.

Also, in the real model, I have a response which is y/time (like in 
lm(y/time~x1 + x2,...) ) , but if I put the time variable at the right side 
(lm(y~I(x1 + x2)*time) , it gets an coefficient.
Is there a way to avoid this?

Thanks


Bart