sandsky <[EMAIL PROTECTED]> wrote:
> I think that IWLS provides the computational flexibility. Because when there
> exists no analytical solution, IWLS makes it possible to solve via the
> numerical solution.
>
> Do you have any idea for this?
My impression is the same as yours.
M.H.P.
__
Mike,
Thank you for your valuable reply. I have read Charnes et al. (1976) and
Bradley (1973). However, they just showed the equivalence of IWLS and ML
solutions, but didn't mentioned the advantage (or disadvantage) of IWLS
comparing with ML estimation.
Charnes, A., Frome, E. L., and Yu, P. L.,
sandsky <[EMAIL PROTECTED]> wrote:
> I am thinking about IWLS vs ML estimation. When I use glm() for a
> 2-parameter distribution (e.g., Weibull), I can otain the MLE of scale
> parameter given shape parameter through IWLS. Because this scale parameter
> usually converges to the MLE.
>
> In this
Hi,
I am thinking about IWLS vs ML estimation. When I use glm() for a
2-parameter distribution (e.g., Weibull), I can otain the MLE of scale
parameter given shape parameter through IWLS. Because this scale parameter
usually converges to the MLE.
In this point, I am wondering:
i) can you say th
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