Re: [Quantlib-dev] Hi, I'm the user of QuantLib

[蔡宗儒-風險管理處-銀行 <Jas...@si...>]

Hi dears,
	After survey, I think LM method is goal to "Fitting".

	Hence,in E2 = -1+x+x^2 (the unexpected solution), LM method min the distance between 0 and -1+x+x^2.
	Since LM method is to min the distance instead of function value, as your words, it is not suitable for my problem.

	My conclusion is :
	1.When I want to min the math function, I should not choose LM method.
	2.When I want to do fitting, LM method can do very well.

	In testsuite->optimizers.hpp, LM method is essential different from ConjugateGradient,SteepestDescent or BFGS.
	It is just fortunate to got the min(the example in C# is 1+x+x^2 but not -1+x+x^2).

	Thanks for your help!!
	
Regards,
 
蔡宗儒   Jason Tsai
永豐銀行風險管理處
TEL：81618681
FAX：81618482

-----Original Message-----
From: Luigi Ballabio [mailto:lui...@gm...] 
Sent: Thursday, March 31, 2011 5:02 PM
To: 蔡宗儒-風險管理處-銀行
Cc: Kim Kuen Tang; qua...@li...
Subject: Re: [Quantlib-dev] Hi, I'm the user of QuantLib

On Mon, 2011-03-28 at 10:17 +0800, 蔡宗儒-風險管理處-銀行 wrote:
>     Can you tell me LevenbergMarquardt  in Qunatlib is goal to find 
> min or root?

It should be the min, but I'm afraid that the MINPACK routine it calls stops at a root because it minimizes the sum of squares.
LevenbergMarquardt is probably not the right optimizer for your problem; I suggest you use another.

Luigi


-- 

fix, n.,v. 
What one does when a problem has been reported too many times to be ignored. 
-- the Jargon file