"Exponential regression" takes the input signal and fits an exponential
to it where t is the variable along the x-axis.
The function is based on the function Linear regression, with the y-axis scaled logarithmically.
Return parameters of "Exponential regression" are:
- the amplitude a and
- the exponent b of the exponential fitting function.
Besides a and b, the corresponding uncertainties sigma a and sigma b and the linear correlation coefficient r appear in the message window. This coefficent is given by
where the overline denotes mean values.
Values of r near 0 indicate poor fitting, whereas good fitting is indicated by values of r near +1 or -1, depending on whether the exponent b of the fitting function is positive or negative.
y = ExpRegress(x,&a,&b);
Linear regression, Multilinear regression,
Power regression, Remove DC, Remove trend,
Long term correlation analysis (LTCA), Principal component analysis (PCA), R/S statistics, Box-Cox transform, Detrended fluctuation analysis (DFA).