mcprobtree {mc2d}R Documentation

Creates a Stochastic mcnode Object using a Probability Tree

Description

This function builds a mcnode as a mixture of mcstoc functions or mcnode objects.

Usage

mcprobtree(mcswitch, mcvalues, type=c("V", "U", "VU", "0"), nsv=ndvar(),
          nsu=ndunc(), nvariates=1, outm="each", seed=NULL)

Arguments

mcswitch A vector of probabilities/weights or a mcnode including the mcstoc functions/mcnodes to pick.
mcvalues A named list of mcnode, mcdata functions or mcstoc functions, or a combination of those objects. Each element should lead to an mcnode of type type and of dimension c(nsv x nsu x 1) or c(nsv x nsu x nvariates)
type The type of mcnode to be built. By default, a "V" node. see mcnode for details.
nsv The number of simulations in the variability dimension of the final node.
nsu The number of simulations in the uncertainty dimension of the final node.
nvariates The number of variates of the final mcnode.
outm The default output of the mcnode for multivariates nodes. see outm.
seed The random seed used for the evaluation. If NULL the seed is unchanged.

Details

mcswitch may be:

The elements in mcvalues should be of same type and dimension as specified in type, nsv, nsu and nvariates. The name should correspond to the values in mcswitch, specified as character (See Examples). These elements will be evaluated only if needed : if the corresponding value is not present in mcswitch, the element will not be evaluated.

Value

An mcnode object.

Author(s)

Regis Pouillot

See Also

mcdata, mcstoc, switch.

Examples

## A mixture of normal (prob=0.75), uniform (prob=0.20) and constant (prob=0.05)
conc1 <- mcstoc(rnorm, type="VU", mean=10, sd=2)
conc2 <- mcstoc(runif, type="VU", min=-6, max=-5)
conc3 <- mcdata(0, type="VU")
## Randomly in the cells 
whichdist <- mcstoc(rempiricalD, type="VU", values=1:3, prob= c(.75, .20, .05)) 
mcprobtree(whichdist, list("1"=conc1, "2"=conc2, "3"=conc3), type="VU")
## Which is equivalent to 
mcprobtree(c(.75, .20, .05), list("1"=conc1, "2"=conc2, "3"=conc3), type="VU")
## Not that there is no control on the exact number of occurences.

## Randomly by colums (Uncertainty) 
whichdist <- mcstoc(rempiricalD, type="U", values=1:3, prob= c(.75, .20, .05)) 
mcprobtree(whichdist, list("1"=conc1, "2"=conc2, "3"=conc3), type="VU")

## Randomly by line (Variability) 
whichdist <- mcstoc(rempiricalD, type="V", values=1:3, prob= c(.75, .20, .05)) 
mcprobtree(whichdist, list("1"=conc1, "2"=conc2, "3"=conc3), type="VU")


[Package mc2d version 0.1-5 Index]