# [R] Failure in predicting parameters

Luigi Marongiu m@rong|u@|u|g| @end|ng |rom gm@||@com
Mon Mar 15 07:39:26 CET 2021

```Hello,
the negative data comes from the machine. Probably I should use raw
data directly, although in the paper this requirement is not reported.
The p\$x was a typo. Now I corrected it and I got this error:
```

> rutledge_param <- function(p, x, y) ((p\$M / (1 + exp(-1*(x-p\$m)/p\$s))) + p\$B) - y
> estim <- nls.lm(par = list(m = halfFluo, s = slopes, M = MaxFluo, B = high[1]),
+             fn = rutledge_param, x = 1:45, y = high)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
```
Probably because 'slopes' is a vector instead of a scalar. Since the
slope is changing, I don't think is right to use a scalar, but I tried
and I got:
```
> estim <- nls.lm(par = list(m = halfFluo, s = 1, M = MaxFluo, B = high[1]),
+             fn = rutledge_param, x = 1:45, y = high)
> estim
Nonlinear regression via the Levenberg-Marquardt algorithm
parameter estimates: 6010.94, 1, 12021.88, 4700.49288888889
residual sum-of-squares: 1.14e+09
reason terminated: Relative error in the sum of squares is at most `ftol'.
```
The values reported are the same I used at the beginning apart from
the last (the background parameter) which is 4700 instead of zero. If
I plug it, I get an L shaped plot that is worse than that at the
beginning:
```
after = init = rutledge(halfFluo, 1, MaxFluo, 4700.49288888889, high)
points(1:45, after, type="l", col="blue")
```
What did I get wrong here?
Thanks

On Sun, Mar 14, 2021 at 8:05 PM Bill Dunlap <williamwdunlap using gmail.com> wrote:
>
> > rutledge_param <- function(p, x, y) ((p\$M / (1 + exp(-1*(p\$x-p\$m)/p\$s))) + p\$B) - y
>
> Did you mean that p\$x to be just x?  As is, this returns numeric(0)
> for the p that nls.lm gives it because p\$x is NULL and NULL-aNumber is
> numeric().
>
> -Bill
>
> On Sun, Mar 14, 2021 at 9:46 AM Luigi Marongiu <marongiu.luigi using gmail.com> wrote:
> >
> > Hello,
> > I would like to use the Rutledge equation
> > (https://pubmed.ncbi.nlm.nih.gov/15601990/) to model PCR data. The
> > equation is:
> > Fc = Fmax / (1+exp(-(C-Chalf)/k)) + Fb
> > I defined the equation and another that subtracts the values from the
> > expectations. I used minpack.lm to get the parameters, but I got an
> > error:
> > ```
> >
> > > library("minpack.lm")
> > > h <- c(120.64, 66.14, 34.87, 27.11, 8.87, -5.8, 4.52, -7.16, -17.39,
> > +        -14.29, -20.26, -14.99, -21.05, -20.64, -8.03, -21.56, -1.28, 15.01,
> > +        75.26, 191.76, 455.09, 985.96, 1825.59, 2908.08, 3993.18, 5059.94,
> > +        6071.93, 6986.32, 7796.01, 8502.25, 9111.46, 9638.01, 10077.19,
> > +        10452.02, 10751.81, 11017.49, 11240.37, 11427.47, 11570.07, 11684.96,
> > +        11781.77, 11863.35, 11927.44, 11980.81, 12021.88, 12058.35, 12100.63,
> > +        12133.57, 12148.89, 12137.09)
> > > high <- h[1:45]
> > > MaxFluo <- max(high)
> > > halfFluo <- MaxFluo/2
> > > halfCycle = 27
> > > find_slope <- function(X, Y) {
> > +   Slope <- c(0)
> > +   for (i in 2:length(X)) {
> > +     delta_x <- X[i] - X[i-1]
> > +     delta_y <- Y[i] - Y[i-1]
> > +     Slope[i] <- delta_y/delta_x
> > +   }
> > +   return(Slope)
> > + }
> > > slopes <- find_slope(1:45, high)
> > >
> > > rutledge <- function(m, s, M, B, x) {
> > +   divisor = 1 + exp(-1* ((x-m)/s) )
> > +   y = (M/divisor) + B
> > +   return(y)
> > + }
> > > rutledge_param <- function(p, x, y) ((p\$M / (1 + exp(-1*(p\$x-p\$m)/p\$s))) + p\$B) - y
> > >
> > >
> > > init = rutledge(halfFluo, slopes, MaxFluo, 0, high)
> > > points(1:45, init, type="l", col="red")
> > > estim <- nls.lm(par = list(m = halfFluo, s = slopes, M = MaxFluo, B = high[1]),
> > +                 fn = rutledge_param, x = 1:45, y = high)
> > Error in nls.lm(par = list(m = halfFluo, s = slopes, M = MaxFluo, B =
> > high[1]),  :
> >   evaluation of fn function returns non-sensible value!
> > ```
> >
> > Where could the error be?
> >
> >
> > --
> > Best regards,
> > Luigi
> >
> > ______________________________________________
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