# converg: Graph of Running Statistics in the Variability or in the... In mc2d: Tools for Two-Dimensional Monte-Carlo Simulations

## Description

This function provides basic graphs to evaluate the convergence of a node of a `mc` or a `mccut` object in the variability or in the uncertainty dimension.

## Usage

 ```1 2 3``` ```converg(x, node=length(x), margin=c("var", "unc"), nvariates=1, iter=1, probs=c(0.025, 0.975), lim=c(0.025, 0.975), griddim=NULL, log=FALSE) ```

## Arguments

 `x` A `mcnode` object, a `mc` object or a `mccut` object. `node` The node to be considered in a mc object or a mccut object, displayed either as the order number or the name of the node. By default: the last node of the object.The corresponding node should not be of type "0" in a mc object or of type "0" or "V" in a mccut object. `margin` The margin used to plot the graph. margin is used only if the node is a "VU" mcnode. `nvariates` The variates to be considered. nvariates is used only for multivariates nodes. `iter` If margin == "var" and the node is a "VU" mcnode, iter specify the iteration in the uncertainty dimension to be used for the graph. `probs` The quantiles to be provided in the variability dimension. `lim` The quantiles to be used in the uncertainty dimension. `griddim` A vector of two integers, indicating the size of the grid of the graph. If NULL, the grid is calculated to produce a "nice" graph. `log` If TRUE, the data will be log transformed.

## Details

If the node is of type "V", the running mean, median and probs quantiles according to the variability dimension will be provided. If the node is of type "VU" and margin="var", this graph will be provided on one simulation in the uncertainty dimension (chosen by iter).

If the node is of type "U" the running mean, median and lim quantiles according to the uncertainty dimension will be provided.

If the node is of type "VU" (with margin="unc" or from a mccut object), one graph are provided for each of the mean, median and probs quantiles calculated in the variability dimension.

## Note

This function may be used on a mccut object only if a summary.mc function was used in the third block of the `evalmccut` call. The values used as probs arguments in converg should have been used in the summary.mc function of this third block.

## Examples

 ```1 2 3``` ```data(total) converg(xVU, margin="var") converg(xVU, margin="unc") ```

### Example output  ```Loading required package: mvtnorm

Attaching package: 'mc2d'

The following objects are masked from 'package:base':

pmax, pmin

Convergence for xVU, variates: 1
Iteration #1 in the uncertainty dimension
Legend:
thick blue = running mean
thick red = running median
thin red = 0.025 0.975 running quantiles
... in the variability dimension
Convergence for xVU, variates: 1
Each graph draws the evolution in the uncertainty dimension of a statistics calculated on the variability dimension
Legend:
thick blue = running mean
thick red = running median
thin red = 0.025 0.975 running quantiles
... in the uncertainty dimension
```

mc2d documentation built on July 5, 2021, 5:09 p.m.