\begin{table}[H]
\centering
\caption{OLS fit and Moran's $I$ test on OLS residuals, by segment}
\label{tab:moran}
\begin{threeparttable}
\begin{tabular}{lrcccc}
\toprule
Segment & $N$ & Adjusted $R^2$ & Moran's $I$ & $z$-statistic & $p$-value \\
\midrule
Single-family houses & 6,250 & 0.619 & 0.506 & 51.9 & $<0.001$ \\
Condominiums & 1,031 & 0.669 & 0.551 & 22.0 & $<0.001$ \\
Multiplexes & 3,755 & 0.576 & 0.528 & 40.2 & $<0.001$ \\
Vacant land & 9,239 & 0.154 & 0.580 & 67.2 & $<0.001$ \\
\bottomrule
\end{tabular}
\begin{tablenotes}
\small
\item \textit{Notes:} OLS estimates of equation~\eqref{eq:hedonic} with HC3 standard errors. Moran's $I$ uses the row-standardised inverse-distance $k$-nearest-neighbour matrix ($k = 10$) of equation~\eqref{eq:W}; the $z$-statistic uses the randomisation (kurtosis-adjusted) variance of \citet{cliff1981spatial}; $p$-values are two-sided normal. All entries are parsed from \texttt{results/sqr\_multi\_segment\_output.txt}, the preserved log of the original run of \texttt{scripts/05\_sqr\_multi\_segment.py}, by \texttt{scripts/06\_tables\_figures\_from\_log.py}.
\end{tablenotes}
\end{threeparttable}
\end{table}