# summary.mc: Summary of mcnode and mc Object In mc2d: Tools for Two-Dimensional Monte-Carlo Simulations

## Description

Provides a summary of a mcnode, a mc or a mccut object.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ```## S3 method for class 'mc' summary(object, probs=c(0, 0.025, 0.25, 0.5, 0.75, 0.975, 1), lim=c(0.025, 0.975), ...) ## S3 method for class 'mcnode' summary(object, probs=c(0, 0.025, 0.25, 0.5, 0.75, 0.975, 1), lim=c(0.025, 0.975), digits=3, ...) ## S3 method for class 'mc' print.summary(x, digits=3, ...) ## S3 method for class 'mccut' summary(object, lim=c(0.025, 0.975), ...) ```

## Arguments

 `object` a mcnode or a mc object or a mccut object. `x` A summary.mc object as provided by the summary.mc function. `probs` A vector of values used for the quantile function (variability dimension). `digits` Number of digits in the print. `lim` A vector of values used for the quantile function (uncertainty dimension). `...` For generic functions consistancy.

## Details

The mean, the standard deviation and the probs quantiles will be evaluated in the variability dimension. The median, the mean and the lim quantiles will then be evaluated on these statistics in the uncertainty dimension.

Multivariate nodes:

If the "outm" attributes of the mcnode is "none", the node is not evaluated, if it is "each" the variates are evaluated one by one, if it is a function (e.g. "mean"), the function is applied on the nvariates dimension before providing a classical output.

## Value

a list.

`mcnode` for mcnode objects, `mc` for mc objects, `mccut` for mccut objects, `quantile`
 ```1 2 3``` ```data(total) summary(xVUM3) summary(total) ```