Hello everybody, I had the following problem. I wanted to make a nonlinear fit of some data. I used the function lsqcurvefit for this obtaining good results. Unfortunately the function didn't output also the errors o the parameters and the goodness of the fit. I turned then to teh function fitnlm t get the errors and the p-values. the output of the function in my case is the following:
mdl = Nonlinear regression model: y ~ 1/(p1*pi)*erf(2/p2*(xdata - p3)) + p4*xdataEstimated Coeff: ________Est___________________SE___________________tStat_________________p-Value p1 35.0596860208699 1.36289657792749 25.7243921429343 3.53913692983459e-11 p2 126.391761700049 8.82277996474738 14.3256164389302 1.84776026703891e-08 p3 21.7624312682344 1.37103425460148 15.8730033149756 6.27414889294585e-09 p4 6.14006005505809e-05 1.57649921913032e-06 38.947434800794 3.87121533656818e-13Number of observations: 15, Error degrees of freedom: 11Root Mean Squared Error: 0.000254R-Squared: 0.999, Adjusted R-Squared 0.999F-statistic vs. zero model: 2.1e+04, p-value = 2.86e-21
Now I don't understand exactly what stands SE for (Squared Errors?). Is it the error on the parameter? or it is the square of it? Or it is something else?
Thanks for the help
Regards
Gabriele
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