The third purpose of this paper is to describe a least squares fitting procedure for obtaining the new drag functions from observed experimental data.

The fitting procedure is relatively troublesome and not popular with tyre fitters.

This bias is not likely not to be an artifact of the fitting procedure.

Several so-called regularization techniques reduce this overfitting effect by constraining the fitting procedure.

This means that iterative non-linear fitting procedures need to be used in place of linear least squares.

The iterative proportional fitting procedure essentially manipulates contingency tables to match altered joint distributions or marginal sums.

The details of the fitting procedure are described in ref.

The fitting procedure assumed a gamma error structure, appropriate for data with constant coefficient of variation, and utilized iterative reweighting of errors.

Unlike a physical model, the parameters in an empirical model need have no fundamental basis, and will depend on the fitting procedure used to find them.

The fitting procedure has not changed since the company was founded in 1926.