Get the coefficient of determination (R²) of the model. The R² goodness of fit is a number between 0 and 1 that measures how well a model predicts the data. A value of 1 means a perfect fit. If all dependent data, the y values, have the same variance the R² is simply 1 - SS_model/SS_total, where SS_model is the sum of the squared differences between y's predicted by the model and the actual y values from the data, and SS_total the sum of the squared differences between the actual data y values and the mean of the data.

Because our data points can have different weights we use adapted formula from Buse (1973).