Is the nls() algorithm based on a weighted non-linear least squares -- I
noticed you mentioned a weighted gradient matrix?
Glenn
Katharine Mullen wrote:
>sorry, the below should read:
>
> A QR decomposition is done on the weighted gradient matrix; if the
>
>
>>estimate of the rank that resul
sorry, the below should read:
A QR decomposition is done on the weighted gradient matrix; if the
> estimate of the rank that results is less than min( the number of
columns in
> the gradient (the number of nonlinear parameters), the
number
> of rows (the number of observations) ) , nls stops.
s
A QR decomposition is done on the weighted gradient matrix; if the
estimate of the rank that results is less than the number of columns in
the gradient (the number of nonlinear parameters), or less than the number
of rows (the number of observations), nls stops.
You can see the calls in the source
//Referring to the response posted many years ago, copied below, what
is the specific criterium used for singularity of the gradient matrix?
Is a Singular Value Decomposition used to determine the singular
values? Is it the gradient matrix condition number or some other
criterion for determ
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