Plots can usually be downloaded by clicking the icon
next to the image. The image is
saved in the Scalable Vector Graphics (SVG) file-format,
which allows arbitrary resizing and editing without degrading the
image quality. You can edit the image using the free software
Inkscape
which can also convert the image to other formats.
Data from some plots can be copied into probability distributions
that can be used in other simulations. Look for the icons
and
next to the plot.
This plot shows a histogram where the bars indicate the density
of data-points.
The red curve smoothly estimates the probability distribution
using KDE.
The blue curve shows the best-fitting normal-distribution.
The red box at the bottom shows the probability of loss, i.e.
the fraction of data-points that are negative.
The background is green for gains and red for losses.
This plot shows a 2-dimensional histogram, where the shades of
cornflower blue
indicate the density of data-points in a region, so that darker
blues indicate regions with higher concentrations of data-points.
The x-axis typically shows varying inputs for the simulation model,
and the y-axis shows the corresponding simulation results.
The red box at the bottom shows the probability of loss,
for the value on the x-axis that is marked as a dashed blue line.
The background is green for gains and red for losses.
This is a violin-plot which shows the KDE smoothened probability
distribution for each future year.
Each probability distribution is just a KDE curve that has been
rotated 90 degrees so we can fit more distributions in a single
plot, and also mirrored so it looks nicer.
These are often shown with a simplified box-plot inside, which can
make them look like violins (and something else we can't quite recall,
but we might have seen a long time ago).
If there are negative values or losses in some distributions, then
the red boxes at the bottom show the probability of loss for each,
i.e. the fraction of data-points that are negative.
The background is green for gains and red for losses.
