[Rd] nls with algorithm = "port", starting values

[Prof Brian Ripley]

I think we should fix the code to do as the documentation says: all it 
needs is an unlist().

Thank you for the examples, which helped test this.

On Mon, 16 Apr 2007, Katharine Mullen wrote:

> The documentation for nls says the following about the starting values:
>
> start: a named list or named numeric vector of starting estimates.
>          Since R 2.4.0, when 'start' is missing, a very cheap guess
>          for 'start' is tried (if 'algorithm != "plinear"').
>
> It may be a good idea to document that when algorithm = "port", if start
> is a named list, the elements of the list must be numeric vectors of
> length 1.  Ie, start = list(a=1,b=2,c=3) is ok, but start = list(a=c(1,2),
> b=3) is not.  This is not the case when algorithm is "plinear" or the
> default GN, and is because of the way that the "port" code in nls.R
> transforms the starting values (the other options do something else):
>
> nls_port_fit <- function(m, start, lower, upper, control, trace)
> {
>    ## Establish the working vectors and check and set options
>    p <- length(par <- as.double(start))
>
>
> Example:
>
> ## exponentially decaying data
> getExpmat <- function(theta, t)
> {
>        conc <- matrix(nrow = length(t), ncol = length(theta))
>        for(i in 1:length(theta)) {
>                conc[, i] <- exp(- theta[i] * t)
>        }
>        conc
> }
>
> expsum <- as.vector(getExpmat(c(.05,.005), 1:100) %*% c(1,1))
> expsumNoisy <- expsum + max(expsum) *.001 * rnorm(100)
> expsum.df <-data.frame(expsumNoisy)
>
> ## estimate decay rates, amplitudes with default Gauss-Newton
> summary (nls(expsumNoisy ~ getExpmat(k, 1:100) %*% sp, expsum.df, start =
> list(k = c(.6,.02), sp = c(1,2)), trace=TRUE, control =
> nls.control(maxiter=20,
> warnOnly =  TRUE)))
>
> ## won't work with port
> summary (nls(expsumNoisy ~ getExpmat(k, 1:100) %*% sp, expsum.df, start =
> list(k = c(.6,.02), sp = c(1,2)), algorithm = "port",
> trace=TRUE, control = nls.control(maxiter=20,
> warnOnly =  TRUE)))
>
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>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595