plot_hist: Plotting Histograms of a Stressed Model
In spesenti/SWIM: Scenario Weights for Importance Measurement

Description Usage Arguments Value See Also Examples

Plots the histogram of a stressed model component (random variable) under the scenario weights.

plot_hist(
  object,
  xCol = 1,
  wCol = "all",
  base = FALSE,
  x_limits,
  displ = TRUE,
  binwidth,
  displLines = FALSE
)

`object`	A `SWIM` or `SWIMw` object.
`xCol`	Numeric or character, (name of) the column of the underlying data of the `object` (`default = 1`).
`wCol`	Vector, the columns of the scenario weights of the `object` corresponding to different stresses (`default = "all"`).
`base`	Logical, if `TRUE`, statistics under the baseline are also returned (`default = "FALSE"`).
`x_limits`	Vector, the limits of the x-axis of the plot, the value for `xlim` in the `coord_cartesian` function in `ggplot`.
`displ`	Logical, if `TRUE` the plot is displayed, otherwise the data.frame for customised plotting with `ggplot` is returned (`default = TRUE`).
`binwidth`	Numeric, the width of the bins used to plot the histogram, the `binwidth` in the `geom_freqpoly` function in `ggplot` (default corresponds to 30 bins).
`displLines`	Logical, if `TRUE` lines are displayed instead of bins (`default = FALSE`).

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 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.

## 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)