R help - May 2003 - Plot observed vs. fitted values (weighted nls)

Dear WizaRds,

Given the experimental data,

csdata<-data.frame(
time=c(0,1,3,9,20),
conc=c(638.697,395.69,199.00,141.58,112.16)
)

weighted nls is applied,

wt.MM<- function(resp, time,A1,a1,A2,a2)
{
    pred <- A1*exp(-a1*time)+A2*exp(-a2*time)
    (resp - pred) / sqrt(pred)
}
#
cs.wt <- nls( ~ wt.MM(conc, time,A1,a1,A2,a2), data=csdata,
              start=list(A1=700,a1=1,A2=100,a2=0.1),
             trace = TRUE)
             
x<-csdata$time
y<-csdata$conc

Now, I want a plot of the observed vs. fitted values. I used
# 1. 'seq' to generate series of values for x-axis
# 2. 'predict' to calculate the fitted values
# 3. 'lines' to overlay the smooth curve of the fitted values

smoothx<-seq(0,20,0.1)

smoothy<-predict(cs.wt,list(x=smoothx))


*Unfortunately, this did not work.

My goal was to use

plot(x,y)
lines(smoothx,smoothy)

Got--Error in xy.coords(x, y) : x and y lengths differ--

ANY SUGGESTIONS? PLEASE:-)

I noticed that
> smoothy<-predict(cs.wt,list(x=smoothx))
> smoothy
[1] -0.15787479  0.38479197 -0.43312824  0.29216236 -0.09731213

is not a correct prediction of the response based on the results. 

The following was obtained using S-PLUS (which I really do not want to be using)
> predict(cs.wt)
[1] 640.2268 390.9596 205.7743 136.1417 114.0573


Kindest Regards and Many Thanks in Advance

Oscar A. Linares
The Geriatrics Center
University of Michigan, Ann Arbor

On Wed, 21 May 2003 DivineSAAM at aol.com wrote:
> Dear WizaRds,
>
> Given the experimental data,
>
> csdata<-data.frame(
> time=c(0,1,3,9,20),
> conc=c(638.697,395.69,199.00,141.58,112.16)
> )
>
> weighted nls is applied,
>
> wt.MM<- function(resp, time,A1,a1,A2,a2)
> {
>     pred <- A1*exp(-a1*time)+A2*exp(-a2*time)
>     (resp - pred) / sqrt(pred)
> }
> #
> cs.wt <- nls( ~ wt.MM(conc, time,A1,a1,A2,a2), data=csdata,
>               start=list(A1=700,a1=1,A2=100,a2=0.1),
>              trace = TRUE)
>
> x<-csdata$time
> y<-csdata$conc
>
> Now, I want a plot of the observed vs. fitted values. I used
> # 1. 'seq' to generate series of values for x-axis
> # 2. 'predict' to calculate the fitted values
> # 3. 'lines' to overlay the smooth curve of the fitted values
>
> smoothx<-seq(0,20,0.1)
>
> smoothy<-predict(cs.wt,list(x=smoothx))
predict()  is looking for a variable called "time".
Try  predict(cs.wt, data.frame(time=seq(0,20,0.1)))
>
> *Unfortunately, this did not work.
>
> My goal was to use
>
> plot(x,y)
> lines(smoothx,smoothy)
>
> Oscar A. Linares
> The Geriatrics Center
> University of Michigan, Ann Arbor
>
-  tom blackwell  -  u michigan medical school  -  ann arbor  -