Non Linear Regression: Power Curve
Assuming that our model is power curve , we can take logarithm to both sides of the equation.
To compute manually, we take logarithm to both and . Thus, we have model transformation and .
Then we plot log x versus log y and if the data is fit into a power curve, we will obtain a linear model in the double log plot. For our data we find with R-squared of 0.9999. Thus, the data fits into power curve. The parameters of the power curve can be obtained from the linear model using parameter transformation and . In this case, we have or . Thus, the regression line is with the same R-squared of 0.9999