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<p class=MsoNormal><span lang=EN-US>Hello everybody,<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US>I’m interested in rating premium insurance,
with the idea to implement under R the theory linked in the paper attached (only
hypothesis=distribution belongs to family exponential,<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US>No a priori specification)<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>I’ve already have a gauss (software named…)
code which do this with a package named CML (constrained maximum likehood).<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>With R, I’ve searched similar pack/functions
like nlminb, maxLik and optim or other function in which I can precise
the analytic function of loglik, gradient and hessian related to family exponential.<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US>But with no success (Newton raphson
unavaible with fixes gr/hessian (own mistake ?) , often some problem of memory
(matrix size : 550 000 rows x 14 covariables, and finally not sure
that it concerned pseudo likehood.<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>Could Tweedie cover this kind of
preoccupation?<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>Anyone has try with R do to this ?<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>Thanks for your help .<o:p></o:p></span></p>
<p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p>
<p class=MsoNormal><span lang=EN-US>E.ratiarison<o:p></o:p></span></p>
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