summary.SWIM: Summarising Stressed Models
In spesenti/SWIM: Scenario Weights for Importance Measurement

Description Usage Arguments Value Functions Author(s) See Also Examples

This function is a methods for an object of class SWIM or SWIMw. Provides summary statistics of the stochastic model, stressed using the scenario weights.

## S3 method for class 'SWIM'
summary(object, ..., xCol = "all", wCol = "all", base = FALSE)

## S3 method for class 'SWIMw'
summary(object, ..., xCol = "all", wCol = "all", base = FALSE)

`object`	A `SWIM` or `SWIMw` object.
`...`	Additional arguments will be ignored.
`xCol`	Numeric or character vector, (names of) the columns of the underlying data of the `object` (`default = "all"`).
`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"`).

summary.SWIM returns a list with components corresponding to different stresses. Components contain a summary statistic of each column of the data of the SWIM object:

`mean`	The sample mean.
`sd`	The sample standard deviation.
`skewness`	The sample skewness.
`ex kurtosis`	The sample excess kurtosis
`1st Qu.`	The 25% quantile.
`Median`	The median, 50% quantile.
`3rd Qu.`	The 75% quantile.

summary.SWIM: Summarising Stressed Models
summary.SWIMw: Summarising Stressed Models

Silvana M. Pesenti

Zhuomin Mao

summary, SWIM

     
## Example with the Relative Entropy
## continuing example in stress_VaR 
set.seed(0)
x <- as.data.frame(cbind(
  "normal" = rnorm(1000), 
  "gamma" = rgamma(1000, shape = 2)))
  
res1 <- stress(type = "VaR", x = x, 
  alpha = 0.9, q_ratio = 1.05)
summary(res1, xCol = "normal", base = TRUE) 


     
## Example with the Wasserstein distance 
## Not run: 
resW <- stress_wass(type = "RM", x = x, 
alpha = 0.9, q_ratio = 1.05)
summary(resW, xCol = "normal", base = TRUE) 

## End(Not run)