> # 1. Supplying the derivatives results in convergence:
> lgmg <- function(a, b, C0, m, V) {
+ e <- expression((V + b * m * a + C0 * V * b - ((C0 * V * b)^2 + 2 *
+ C0 * b * V^2 - 2 * C0 * V * m * a * b^2 + V^2 + 2 * V * m *
+ a * b + (b * m * a)^2))/(2 * b * m))
+ val <- eval(e)
+ attr(val, "gra
Hi Benoit,
another way of making Petr's point is by looking at the profile log likelihood
function
for b; that is, only estimating the a parameter for a grid of b values:
## Defining mean function for fixed b
lgma <- function(b){
function(C0, m, V, a){ (V + b * m * a + C0 * V * b - ((C0 *
ption of a compound onto activated carbon. I need to assess these
> parameters.
>
>
> Regards/Cordialement
>
>
> Benoit Boulinguiez
>
>
> -Message d'origine-
> De : Petr PIKAL [mailto:[EMAIL PROTECTED]
> Envoyé : mercredi 3 septembre 2008 1
rcredi 3 septembre 2008 17:58
À : Benoit Boulinguiez
Cc : r-help@r-project.org
Objet : Odp: [R] nls convergence trouble
Hi
Excel fit is not exceptionally good. Try
fff<-function(a,b) (V + b * m * a + C0 * V * b - ((C0 * V * b)^2 + 2 * C0
*
+ b * V^2 - 2 * C0 * V * m * a * b^2 + V^2 + 2 * V * m *
Try squaring both sides of the formula.
On Wed, Sep 3, 2008 at 10:01 AM, Benoit Boulinguiez
<[EMAIL PROTECTED]> wrote:
> Hi,
>
> Parameters assessment in R with nls doesn't work, though it works fine with
> MS Excel with the internal solver :(
>
>
> I use nls in R to determine two parameters (a,b)
Hi,
Parameters assessment in R with nls doesn't work, though it works fine with
MS Excel with the internal solver :(
I use nls in R to determine two parameters (a,b) from experimental data.
m VC0 CeQe
1 0.0911 0.0021740 3987.581 27.11637 94.5120
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