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Drop inlabru in vignette
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vignettes/articles/forecasting.Rmd

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@@ -299,10 +299,9 @@ ggplot(newdf, aes(x, y)) +
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We can also visualize uncertainty in the forecasts by mapping the standard error of predicted densities at each point in space.
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We see that uncertainty is higher at vertices.
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This is because there are fewer neighbors, e.g. [this tutorial](https://ourcodingclub.github.io/tutorials/spatial-modelling-inla/)
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```{r vis-vert}
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ggplot() +
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inlabru::gg(mesh$mesh) +
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geom_point(data = p, aes(x = x, y = y, col = est_se)) +
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coord_equal() +
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labs(col = "Standard error\nof spatiotemporal field")

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