uncertainty and curve fitting

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Mira
Mira el 19 de Dic. de 2011
Hi,
Please I need your help. I'm working on curve fitting, I'm using lsqcurvefit function to do it!! I'm trying to estimate uncertainty of the coefficient A and B of the function fitted to my observation ponits (y=A.x^B)!! Please could you help me!! Thank you in advance
Mira

Respuesta aceptada

Richard Willey
Richard Willey el 19 de Dic. de 2011
If you need confidence intervals nlinfit is a better option

Más respuestas (2)

bym
bym el 19 de Dic. de 2011
this example shows how to bootstrap to get the standard error in the coefficients. You can adapt it to use lsqcurvefit or transform your model to linear using logarithms
load hald
x = [ones(size(heat)),ingredients];
y = heat;
b = regress(y,x);
yfit = x*b;
resid = y - yfit;
se = std(bootstrp(...
1000,@(bootr)regress(yfit+bootr,x),resid));
  1 comentario
Richard Willey
Richard Willey el 20 de Dic. de 2011
Bootstraps are great. I love them to death. However, I question whether they're an appropriate solution when parametric methods are available.
In general, I think of bootstraps as something we do out of necessity when a parametric estimate isn't feasible. For example, generating confidence bounds around the median, bootstrapping a LOESS curve or a kernel smoother.

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Mira
Mira el 20 de Dic. de 2011
Thank you guys for your help. This is exactly what I'm looking for!!! Thanks

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