flux are $\sim 35
\%$, or 0.13 dex.

Estimating errors in line width is more difficult, since uncertainty in the decomposition between broad and narrow components dominates the measurement error. In some cases the separation is obvious, but in others (see, e.g., the top panel of Fig. 1) there is no clear distinction between the two components. We generate an artificial spectrum for each object by combining the best-fit model emission lines and Gaussian random errors with matching S/N. An artificial spectrum generated in this manner will suffer from the same decomposition ambiguity as the original data. We then fit these artificial spectra using our fitting procedure, as outlined above. The estimated uncertainty is simply taken to be the difference between the model and measured FWHM. We find that S/N significantly impacts the reliability of our fits. While typical errors are $\sim 7 \%$ (or 0.03 dex) and $\sim 10 \%$ (0.05 dex) for [$\mathrm{FWHM}_\mathrm{H{\alpha}}$]{} and [$\mathrm{FWHM}_\mathrm{H{\beta}}$]{}, respectively, these are found to increase to as much as 0.1 dex in cases with the lowest S/N.

Results
=======

Empirical Correlations
----------------------

Our data reveal a well-defined correlation between Balmer emission-line luminosity and [$L_{5100}$]{}. This is illustrated in Figure 2, which includes 