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Please can people advise me on this!

  1. Jul 9, 2011 #1
    Hi I have attached an image of part of a freely available paper I was reading. It shows the equations for least squares minimization of some equations based on empirical data.

    I am not completely confident I understand the required steps, and therefore just wanted to talk it through with others, see what you say and see if it sparks any ideas to solve these.

    As I understand it, the first equation (eqn 40) is minimizes using levenberg marquardt for a, b and c0. k is 1,2,3,4..... t_k is times stored, the rest of the equation is trying to model the time it will take (whatever that time may be).

    Ok so using levenberg marquardt estimate a, b and c0.
    But the the next equation (eqn 41) says that he freezes beta to be ab^2, and uses golden section method to 'refine' a and b?

    Did the leveneberg marquardt not do a good enough job because I thought we found and ab that way?

    the author also give the sub equations for c0. Why? I thought we estimated c0?

    Ok so however it has been done, we have a good estimate for a, b and c0.
    Eqn 42. Same thing again except now for nu, phi, omega^2.

    How is it explaining to solve this?
    "robus linear estimation"? "Directly minimizing"? Is that how? Why cant we use levenberg marquardt again?

    I just would like discussion, Im not after just the answer, I would like to understand when to use what, and why...

    Thanks guys

    By the way, that is the whole chapter I havent left anything out except the chapter title

    Attached Files:

    Last edited: Jul 9, 2011
  2. jcsd
  3. Jul 9, 2011 #2
    Is this in the wrong forum?
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