[R] Problem with logarithmic nonlinear model using nls() from the `stats' package

[Casper Ti. Vector]

Ah, now I see...
Thanks very much :)

On Sat, Oct 01, 2011 at 09:27:34AM -0400, Gabor Grothendieck wrote:
> On Sat, Oct 1, 2011 at 5:28 AM, Casper Ti. Vector
> <caspervector at gmail.com> wrote:
> Its linear given c so calculate the residual sum of squares using lm
> (or lm.fit which is faster) given c and optimize over c:
> 
> set.seed(123) # for reproducibility
> x <- 1:10
> y <- 1 + 2 * log(1 + 3 * x) + rnorm(1, sd = 0.5)
> fitc <- function(c) lm.fit(cbind(1, log(1 + c * x)), y)
> rssvals <- function(c) sum(resid(fitc(c))^2)
> out <- optimize(rssvals, c(0.01, 10))
> 
> which gives:
> 0.7197666 2.0000007 2.9999899

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