Curve Fit
The curve fit calculation determines a logarithmic curve, an exponential curve, or a polynomial of specified order that fits the selected Data Series. The polynomial is found by minimizing the sum of the squared differences between the selected Data Series and the polynomial (minimum mean square error).
In the script, this calculation is done very simply. The polynomial curve is found using the built in function polyFit(order), which is called on the input data series. The logarithmic curve is found by taking the exponential of the data with built in function exp(e). A first order polynomial is then fit to this data using the polyFit function again, and the natural log is taken of this result using the built in function ln(), which gives us the best fit logarithmic curve. The exponential curve is taken in a similar manner, except that the natural log is taken on the input data series, then a first order polynomial is fit to this data, the result of which is raised to the power e to give the best fit exponential curve.
Parameters