mc2d (version 0.2.0)

converg: Graph of Running Statistics in the Variability or in the Uncertainty Dimension.

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

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.

Examples

Run this code
data(total)
converg(xVU, margin="var")
converg(xVU, margin="unc")

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