\begin{table}%t4 \caption{\label{tbl:model_evaluation}Model evaluation$^{\dagger}$.} \par \small%\centerline { \begin{tabular}{lccccc} \hline\hline Model & AIC (\%) & BIC (\%) & VR (\%) & PR (\%) &$k$\\ \hline Eq.~(\ref{eq:model2}), fixed comb & \textbf{94.010} & \textbf{94.065} & 97.755 & \textbf{25.50} & 78\\ Eq.~(\ref{eq:model1}), Scargle freqs & 94.023 & 94.171 & 97.761 & 25.49 & 100\\ Eq.~(\ref{eq:model1}), NLLS freqs & 94.021 & 94.169 & \textbf{97.762} & 25.49 & 100\\ \hline Eq.~(\ref{eq:dominant_mode_time_variable}), 1 freq & 95.417 & 95.378 & 96.873 & 30.81 & 40\\ Eq.~(\ref{eq:model1}), Scargle freqs & 95.405 & 95.314 & 96.872 & \textbf{30.87} & 28\\ Eq.~(\ref{eq:model1}), NLLS freqs & \textbf{95.404} & \textbf{95.314} & \textbf{96.872} & 30.85 & 28\\ \hline Eq.~(\ref{eq:dominant_mode_time_variable}), 2 freqs & 95.228 & 95.255 & 97.019 & 30.14 & 58\\ Eq.~(\ref{eq:model1}), Scargle freqs & 95.204 & 95.130 & 97.017 & \textbf{30.24} & 34\\ Eq.~(\ref{eq:model1}), NLLS freqs & \textbf{95.204} & \textbf{95.130} & \textbf{97.017} & 30.22 & 34\\ \hline Eq.~(\ref{eq:dominant_mode_time_variable}), 3 freqs & 94.887 & 97.974 & 97.255 & 28.65 & 76\\ Eq.~(\ref{eq:model1}), Scargle freqs & 94.837 & 94.783 & 97.263 & \textbf{28.84} & 43\\ Eq.~(\ref{eq:model1}), NLLS freqs & \textbf{94.837} & \textbf{94.783} & \textbf{97.263} & 28.82 & 43\\ \hline Eq.~(\ref{eq:dominant_mode_time_variable}), 4 freqs & 94.746 & 94.901 & 97.355 & 27.99 & 94\\ Eq.~(\ref{eq:model1}), Scargle freqs & 94.687 & 94.664 & 97.361 & 28.29 & 52\\ Eq.~(\ref{eq:model1}), NLLS freqs & \textbf{94.687} & \textbf{94.664} & \textbf{97.361} & \textbf{28.29} & 52\\ \hline \end{tabular}} \medskip $\dagger$ The best model according to the four considered statistics are emphasised in~bold. \end{table}