of the GEV parameters at each location and the mean squared error (MSE) of the posterior means (averaged over the $n$ sites for the spatially-varying GEV location). Figure \[fsim\] plots the $M=50$ root MSEs and coverage probabilities (averaged over sites for the GEV location).

![Boxplots of root mean squared error (RMSE) for the GEV parameters in the simulation study. The horizontal lines in the boxplots are the 0.05, 0.25, 0.50, 0.75, and 0.95 quantiles of RMSE. Coverage percentages of posterior 95% intervals are given below the boxplots.[]{data-label="fsim"}](591f03.eps)

For the data generated with $L_0=25$ or $L_0=49$ knots in Figure \[fsim\](a), the coverage probabilities are generally near the nominal level. With $L=49$ knots, the coverage probabilities range from 0.90 to 0.94 for the GEV location. For the first two designs, the model with $L=25$ knots has fewer knots than were used to generate the data. This does not have a substantial impact on the estimation of the GEV location. However, using too few knots leads to increased RMSE and under-coverage for the GEV log scale, especially for design 1 with strong spatial dependence. For simulation designs 3 and 4, the model with $L=49$ knots has nearly twice as many knots than were 