There seems to be a confusion between error of original fit which is calculated previously whereas fitted error of a fit is the model parameter which is known as MSE (Mean Squared Error). For examples on how to calculate the MSE, read the documentation here.
Fitted error vs error of original fit
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I am asked to compare the fitted error to the error of original fit of a set of data labeled data_valid_fit. Using a given equation I calculated the fitting error as below:
% The data estimated on the validation set with r and y0
valid_data_fit = y0.*exp(r*tvalid)
% Computing fitting error
e = 1/length(t)*sqrt(sum((valid_data_fit - datavalid).^2))
If my function is y= y0*exp(r*t) and I calculated datafit using that function and:
y0= 149.4515
r= 0.0330
t = [ 0, 13, 36, 46, 61, 64, 70, 75, 78].
How can I calculate the error of original fit?
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