This command selects least-squares optimization, i.e., the objective function to be minimized is the sum of the squared weighted residuals.
Minimizing the squared weighted residuals leads to a maximum-likelihood estimate if the errors are normally distributed with zero mean and covariance matrix Czz:
Least-squares estimation is the default. If outliers are more prominent than
described by the tail of the normal distribution, one may want to use one of
the robust estimators to reduce the weight of outliers or even eliminate them
>>> use LEAST-SQUARES