plotCS_un | R Documentation |
Function to generate uncollapsed cross-section plots to visualize changes in the performance metrics of interest
as the proportion of missing data and gap width increase. Instead of three axes, as in the surface plots,
either p
or g
can be broken down such that changes in performance are depicted with respect to one variable,
across each value of the other. The variable to form the x-axis is specified in cross_section
.
Plots are arranged vertically, where each represents performance plotted against each fixed value in the
variable not specified in cross_section
. The middle line is the median value, the upper
ribbon boundary is the 97.5th quantile value, and the lower ribbon boundary is the
2.5th quantile value.
plotCS_un(
agEval,
cross_section = "p",
crit,
d = 1:length(agEval),
m = names(agEval[[1]][[1]][[1]]),
f = "median",
layer_type = "method",
highlight = "HWI",
highlight_color = "#FA4032",
colors = c("#FF8633", "#FFAF33", "#FFD133", "#FFEC33", "#D7FF33", "#96FF33")
)
agEval |
|
cross_section |
|
crit |
|
d |
|
m |
|
f |
|
layer_type |
|
highlight |
|
highlight_color |
|
colors |
|
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