plot_cons_plans {metafolio} | R Documentation |
This makes a mean-variance plot of the portfolio output. It can take care of: plotting the individual portfolios, adding 2D kernel density polygons at two quantile levels, and adding an efficient frontier.
plot_cons_plans(plans_mv, plans_name, cols, xlim = NULL, ylim = NULL, add_pts = TRUE, add_all_efs = FALSE, x_axis = TRUE, y_axis = TRUE, add_legend = TRUE, legend_pos = "topright", w_show = "all", xlab = "Variance", ylab = "Mean", add_poly = TRUE, ...)
plans_mv |
The |
plans_name |
A character vector of what to label each conservation plan. |
cols |
Colours for the conservation plan polygons. |
xlim |
X limits |
ylim |
Y limits |
add_pts |
Logical: add the points? |
add_all_efs |
Logical: add efficient frontiers? |
x_axis |
Logical: add x axis? |
y_axis |
Logical: add y axis? |
add_legend |
Logical: add y legend? |
legend_pos |
A character string to pass to
|
w_show |
If |
xlab |
X axis label. |
ylab |
Y axis label. |
... |
Anything else to pass to
|
add_poly |
Add the kernal smoother quantile polygons? |
A plot. Also, the x and y limits are returned invisibly as a list. This makes it easy to make the first plot and then save those x and y limits to fix them in subsequent (multipanel) plots.