The objective consists of adjusting the parameters of a model function to best fit a data set. A simple data set consists of "n" points (data pairs) formula_1, "i" = 1, …, "n", where formula_2 is an independent variable and formula_3 is a dependent variable whose value is found by observation. The model function has the form formula_4, where "m" adjustable parameters are held in the vector formula_5. The goal is to find the parameter values for the model that "best" fits the data. The fit of a model to a data point is measured by its residual, defined as the difference between the actual value of the dependent variable and the value predicted by the model: