Returns the deviance (residual sum of squares) \(\sum_{i=1}^n \hat d_i^2\) of the fitted, precision-weighted orthogonal distances from the fitted onls model -- the same quantity that onls itself minimizes. See 'Details' for what \(\hat d_i\) represents in general; a single-predictor, unweighted fit is a special case where this reduces to plain squared Euclidean distance.
deviance_o(object)The deviance of the fitted orthogonal (precision-weighted) distances.
an object returned from onls.
Andrej-Nikolai Spiess
\(\hat d_i\) is the fitted, precision-weighted orthogonal distance of observation \(i\) (see 'Details' in onls for its full definition and the construction of \(Qyy_i\), \(Qx_i\) from weights, sigma_x, and sigma_y); it reduces to plain Euclidean distance only for a single-predictor, unweighted fit. deviance_o returns \(\sum_{i=1}^n \hat d_i^2\), numerically identical to sum(residuals_o(object)^2) and to the value onls itself minimized (object$objective).