High Quality Content by WIKIPEDIA articles! Total least squares, also known as errors in variables, rigorous least squares, or (in a special case) orthogonal regression, is a least squares data modeling technique in which observational errors on both dependent and independent variables are taken into account. It is a generalization of Deming regression, and can be applied to both linear and non-linear models.