For the example provided below, the subsetting happens in evaluating the
call to stats::model.formula in line 583 of nls.R
(https://github.com/wch/r-source/blob/e91be22f6f37644e5a0ba74a3dfe504a3a29e9f7/src/library/stats/R/nls.R#L583)
returning an appropriate (subsetted) data frame.
-Naras
On 7/13/21 4:21 PM, J C Nash wrote:
In mentoring and participating in a Google Summer of Code project "Improvements to
nls()",
I've not found examples of use of the "subset" argument in the call to nls().
Moreover,
in searching through the source code for the various functions related to
nls(), I can't
seem to find where subset is used, but a simple example, included below,
indicates it works.
Three approaches all seem to give the same results.
Can someone point to documentation or code so we can make sure we get our
revised programs
to work properly? The aim is to make them more maintainable and provide
maintainer documentation,
along with some improved functionality. We seem, for example, to already be
able to offer
analytic derivatives where they are feasible, and should be able to add
Marquardt-Levenberg
stabilization as an option.
Note that this "subset" does not seem to be the "subset()" function of R.
John Nash
# CroucherSubset.R -- https://walkingrandomly.com/?p=5254
xdata = c(-2,-1.64,-1.33,-0.7,0,0.45,1.2,1.64,2.32,2.9)
ydata =
c(0.699369,0.700462,0.695354,1.03905,1.97389,2.41143,1.91091,0.919576,-0.730975,-1.42001)
Cform <- ydata ~ p1*cos(p2*xdata) + p2*sin(p1*xdata)
Cstart<-list(p1=1,p2=0.2)
Cdata<-data.frame(xdata, ydata)
Csubset<-1:8 # just first 8 points
# Original problem - no subset
fit0 = nls(ydata ~ p1*cos(p2*xdata) + p2*sin(p1*xdata), data=Cdata,
start=list(p1=1,p2=.2))
summary(fit0)
# via subset argument
fit1 = nls(ydata ~ p1*cos(p2*xdata) + p2*sin(p1*xdata), data=Cdata,
start=list(p1=1,p2=.2), subset=Csubset)
summary(fit1)
# via explicit subsetting
Csdata <- Cdata[Csubset, ]
Csdata
fit2 = nls(ydata ~ p1*cos(p2*xdata) + p2*sin(p1*xdata), data=Csdata,
start=list(p1=1,p2=.2))
summary(fit2)
# via weights -- seems to give correct observation count if zeros not recognized
wts <- c(rep(1,8), rep(0,2))
fit3 = nls(ydata ~ p1*cos(p2*xdata) + p2*sin(p1*xdata), data=Cdata,
weights=wts, start=list(p1=1,p2=.2))
summary(fit3)
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