# [R] weights in nls

Douglas Bates bates at stat.wisc.edu
Tue Sep 26 18:41:37 CEST 2000

```Douglas Bates <bates at cs.wisc.edu> writes:

> In the meantime, you can use the approach that John Chambers and I
> describe in chapter 10 of "Statistical Models in S" (a.k.a. the white
> book) and write the model as a one sided formula giving the weighted
> residual.

I should have checked before I wrote that.  A one-sided formula
doesn't work.  You must use a vector of zeroes of the appropriate
length on the left hand side.

> library(nls)
> data(Puromycin)
> nls(rate ~ Vm * conc/(K + conc), data = Puromycin, weights = 1/conc,
+    subset = state == "treated", start = c(Vm = 200, K = 0.05))
Nonlinear regression model
model:  rate ~ Vm * conc/(K + conc)
data:  Puromycin
Vm            K
212.68357970   0.06412103
residual sum-of-squares:  1195.449
> nls(rep(0, length(conc)) ~ (rate - Vm * conc/(K + conc))* sqrt(conc),
+   data = Puromycin, subset = state == "treated", start = c(Vm = 200, K = 0.05))
Nonlinear regression model
model:  rep(0, length(conc)) ~ (rate - Vm * conc/(K + conc)) * sqrt(conc)
data:  Puromycin
Vm            K
218.15162032   0.07471006
residual sum-of-squares:  137.4447
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```