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Re: WeibullDistribution

  • To: mathgroup at smc.vnet.net
  • Subject: [mg42616] Re: WeibullDistribution
  • From: "Robert Nowak" <robert.nowak at ims.co.at>
  • Date: Fri, 18 Jul 2003 05:25:10 -0400 (EDT)
  • Organization: Nextra Telekom GmbH
  • References: <bf5kmd$mib$1@smc.vnet.net>
  • Sender: owner-wri-mathgroup at wolfram.com

Hi Bill,

> The primary disadvantage of using NonlinearFit is the difficulty in
finding the true least squares fit, i.e., the set of paramerters that makes
the summed square error globally minimal. It is often the case there are
several local minina and it is easy for the non-linear algogrithm to get
trapped in a local minima. And the real difficulty is there is no simple way
of determining when this happens.

could it be that problems which are transformable in to equivalent linear
problems (such as in the weilbull case) don't encounter the problem of more
than one local minima ?

>From a practical standpoint, no the linear fit to the transformed problem
is good as is with out adjustments. Generally, the uncertainty in the fitted
parameters is larger than the bias particularly when attempting to find
parameters for a given distribution.

oh yes, but now the quest is for the "BEST" method

regards robert



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