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WalterSchrabmai12-Amethyst
12-Amethyst
June 6, 2016
Solved

SSE vs. ERR variable at a MinERR Solveblock?

  • June 6, 2016
  • 2 replies
  • 4650 views

Hi Friends,

one short Question:

Is - for an nonlinear model - the ERR variable at a MINERR Solve Block the same as the Sum of Squared Errors? (SSE)

I have different values there.

Thanks for helping and answering.

Walter

Best answer by ViktorKorobov

Walter,

Compare SSE and ERR^2.

2 replies

V
ViktorKorobov1-VisitorAnswer
1-Visitor
June 6, 2016

Walter,

Compare SSE and ERR^2.

    W
    Werner_E25-Diamond I
    25-Diamond I
    June 6, 2016

    The attached sheet should help but Viktor already explained the relationship.

    Regards, Werner

      W
      WalterSchrabmai12-AmethystAuthor
      12-Amethyst
      June 6, 2016

      Dear Werner, thanks a lot for your nice sheet. I have adapted it with my model and worked fine. I really a little bit confused why the mentioned sheet will not work.

      Thanks

      Walter

      W
      Werner_E25-Diamond I
      25-Diamond I
      June 6, 2016

      The problem is  your SSE function. It does not use the formal arguments a,b,c on the RHS. It should look like this

      Instead of

      you may also use

      or you may like to define your SSE function that way.

      With any of these methods you get an SSE of 0,062 which seems to be pretty good, especially  compared to the SSE=0,103 you get with the values 35 / 15 / 0.6 from MMA(?)

      You should also plot your fit not only with the MMA parameters but also with the parameters optimized by Mathcad (you don't do so in your sheet.

      Its interesting that the SSE value of 0,62 is the very same for every algorithm chosen (LM, conj.grad, Quasi Newton), but the values it self, especially a.rt change significantly. With pure eye not much difference can be spotted in the plot, though.

      Maybe this means that you are working at the numerical limits? Not sure.

      I am surprised that using the full vector of residuals in minerr

      does not provide better results as it usually does. Using LM we get also 0,062, but completely different values.

      Using Quasi Newton we get quite close to the MMA values but with an SSE of 0,076

      Its interesting to see that argument a seems not to have much influence on the fit curve,

      WE

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