Provides a summary for the parameters of the converged fit, including their standard errors, t values and p values, together with residual standard errors with respect to both the vertical and the orthogonal residuals. See 'Details' for how parameters held fixed in the original onls call, and known_sigma-based scaling, are handled.
# S3 method for onls
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)A list of class "summary.onls", with components:
the model formula.
the vertical residuals (observed minus fitted response at the observed predictors).
residual standard error of the vertical distances.
residual standard error of the orthogonal (precision-weighted) distances.
a length-2 vector, the number of free (non-fixed) parameters and the residual degrees of freedom; sum(df) equals the number of observations.
the unscaled covariance matrix of the free parameters; see 'Details'.
the matched call.
convergence information from onls.
the control settings used, see onls.
information on the handling of NAs.
(identical) matrices of Estimate, Std. Error, t value and Pr(>|t|), one row per parameter (including fixed ones, with NA in the last three columns for those); see 'Details'.
as in object.
as in object.
(only if correlation = TRUE) the correlation matrix of the free parameters only; see 'Details'.
(only if correlation = TRUE) as supplied.
an object returned from onls.
logical. If TRUE, the correlation matrix of the estimated (non-fixed) parameters is returned and printed.
logical. If TRUE, print the correlations in a symbolic form.
further arguments passed to or from other methods.
Andrej-Nikolai Spiess
Fixed parameters. If object was fitted with some parameters held fixed (see onls), those parameters were never estimated: their Estimate is still shown (the fixed value used), but Std. Error, t value and Pr(>|t|) are reported as NA rather than 0/Inf/a spuriously small p-value, matching R's own convention for non-estimated coefficients (e.g. aliased terms in summary.lm). The residual degrees of freedom in df count only the free (non-fixed) parameters, so that df[1] + df[2] equals the number of observations, as in summary.lm/summary.nls. If correlation = TRUE, fixed parameters are dropped from the returned correlation matrix entirely (rather than padded with NA rows/columns), since correlation with a held-fixed constant is not a meaningful quantity.
cov.unscaled. object$vcov was already scaled by onls itself: not at all if known_sigma = TRUE, or by the orthogonal-distance reduced chi-square (object$reduced_chisq) if known_sigma = FALSE. cov.unscaled undoes exactly that scaling (dividing by object$reduced_chisq only in the latter case), so that vcov(object) == cov.unscaled * sigma^2 holds with the appropriate sigma, matching the summary.lm/summary.nls convention. This is not the same quantity as the vertical-residual variance (sigmaONLS^2): the vertical and orthogonal residual sums of squares generally differ, even for an unweighted fit, so cov.unscaled must not be confused with, or derived from, sigmaONLS.