plot_hist {SWIM} | R Documentation |
Plotting Histograms of a Stressed Model
Description
Plots the histogram of a stressed model component (random variable) under the scenario weights.
Usage
plot_hist(
object,
xCol = 1,
wCol = "all",
base = FALSE,
x_limits,
displ = TRUE,
binwidth,
displLines = FALSE
)
Arguments
object |
A |
xCol |
Numeric or character, (name of) the column of the underlying data
of the |
wCol |
Vector, the columns of the scenario weights
of the |
base |
Logical, if |
x_limits |
Vector, the limits of the x-axis of the plot, the
value for |
displ |
Logical, if |
binwidth |
Numeric, the width of the bins used to plot
the histogram, the |
displLines |
Logical, if |
Value
If displ = TRUE
, a histogram of the stochastic model
under the scenario weights.
If displ = FALSE
, a data.frame for customised plotting with
ggplot
. The data.frame contains the columns: the column,
xCol
, of the data of the stressed model, stress
(the stresses) and value
(the values).
Denote by res
the return of the function call, then
ggplot
can be called via:
ggplot(res, aes(x = res[ ,1], y = ..density.., weight = value)))
+ geom_{freqpoly}(binwidth, aes(color = factor(stress))).
See Also
See cdf
and plot_cdf
for
values and plotting of the empirical distribution
function of a stressed model, respectively, and
quantile_stressed
for sample quantiles of
a stressed model.
Examples
## example with a stress on VaR
set.seed(0)
x <- data.frame("gamma" = rgamma(10^5, shape = 2))
res1 <- stress(type = "VaR", x = x,
alpha = c(0.75, 0.95), q_ratio = 1.1)
plot_hist(res1, xCol = "gamma", wCol = 1:2, base = TRUE, binwidth = 0.4)
plot_hist(res1, xCol = "gamma", wCol = 1:2, base = TRUE, binwidth = 0.4, displLines = TRUE)