Dear R-help,
Could you please examine the following code, and see if I have discovered a bug
or not, or am just doing something silly.
I am trying to create a package to do fish stock assessment using the nls() function to
fit the modelled stock size to the various pieces of information that we have. The main
problem with this sort of task is that the number and type of parameters that go into the
model are highly variable between stocks, but the method needs to be
"intelligent" enough to handle this. The way I have chosen to handle this is
through the names in my parameter vector, and using code inside the objective function to
figure out which parameter is which.
The problem I have encountered is that I don't think nls() always passes a
named vector - indeed, after the first set of function evaluations, it drops
the names from the parameters vector altogether. I believe this to be a bug -
it certaintly plays havoc with my code!
As a demonstration of this problem, consider the piece of code below. It is basically
fitting a straight line to some synthetic data (with noise). I have setup the objective
function so that it prints the names of the parameters every time that it is called. As
you can see, the names are there to begin with, but rapidly disappear after the first
"step" is made.
Is this a bug? Or is it intended behaviour? Or is this a completely daft
approach I am taking?
I look forward to your comments.
cheers,
Mark
rm(list=ls())
fitting.fn <-function(x,params) {
#The model - so that it works
y <- params[1] + x*params[2]
#How I would prefer it to work
# y <- params["a"] + x*params["b"]
#Display information about function eval
cat(paste("Evaluation # :",counter,"\t Names :"))
print(names(params))
counter <<- counter +1
return(y)
}
counter <<- 1
data.x <- 1:50
data.y <- pi*data.x + rnorm(50,sd=20)
plot(data.x,data.y)
ips <- c(a=0,b=0)
nls("data.y~fitting.fn(data.x,params)",data=data.frame(data.x,data.y),
start=list(params=ips),trace=TRUE,control=nls.control(tol=1e-8))
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