Effacer les filtres
Effacer les filtres

Error with the matlab curve fitter app

10 vues (au cours des 30 derniers jours)
Imanol Fernandez de arroyabe Zabala
Modifié(e) : dpb le 21 Fév 2023
I have a dataset that can be seen below:
I have an equation that is supposed to somewhat predict these points, and I want to check if it holds up using the custom equation option. However, at the time of choosing such option, I can't use it unless it comes with parameters asociated with it (which then matlab will optimize in order to choose the best fit). I don't want to do this. I want to check how well an established function without parameters can predict the points. Thanks in advance.

Réponses (1)

dpb
dpb le 21 Fév 2023
Modifié(e) : dpb le 21 Fév 2023
The CurveFitter App is simply not designed to be used in this manner.
To do this, you would create a fit object directly with the <cfit> function and set the model and coefficients in the object fields and then use <feval> to evaluate the model over the input points.
Of course, when you do this, then the fit object will not have any of the supporting data available to it for confidence limits, goodness of fit, etc., etc., ... that are automagically populated when the fit function is called and creates the output fit object. You would have to derive all those from the results of the residuals and data points and, of course, there's no guarantee that these will be at all representative of the estimated values would obtain by fitting the model so there's no real justification for anything other than computing the residuals and basic global measures of goodness of fit like R-square or the standard error.
Depending upon the model, it may be simpler to just write an evaluation function directly as an m-file or anonymous function.

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