summary.mcSimulation: Summarize results from Monte Carlo simulation.

In decisionSupport: Quantitative Support of Decision Making under Uncertainty

Summarize results from Monte Carlo simulation.

Description

A summary of the results of a Monte Carlo simulation obtained by the function mcSimulation is produced.

Usage

## S3 method for class 'mcSimulation'
summary(
  object,
  ...,
  digits = max(3, getOption("digits") - 3),
  variables.y = names(object$y),
  variables.x = if (classicView) names(object$x),
  classicView = FALSE,
  probs = c(0, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 1)
)

Arguments

object	An object of class mcSimulation.
...	Further arguments passed to summary.data.frame (classicView=TRUE) or format (classicView=FALSE).
digits	how many significant digits are to be used for numeric and complex x. The default, NULL, uses getOption("digits"). This is a suggestion: enough decimal places will be used so that the smallest (in magnitude) number has this many significant digits, and also to satisfy nsmall. (For the interpretation for complex numbers see signif.)
variables.y	character or character vector: Names of the components of the simulation function (model_function), whose results shall be displayed. Defaults to all components.
variables.x	character or character vector: Names of the components of the input variables to the simulation function, i.e. the names of the variables in the input estimate, whose random sampling results shall be displayed. Defaults to all components.
classicView	logical: if TRUE the results are summarized using summary.data.frame, if FALSE further output is produced and the quantile information can be chosen. Cf. section Value and argument probs. Default is FALSE.
probs	numeric vector: quantiles that shall be displayed if classicView=FALSE.

Value

An object of class summary.mcSimulation.

See Also

mcSimulation, print.summary.mcSimulation, summary.data.frame

decisionSupport documentation built on Oct. 6, 2023, 1:06 a.m.