mcprobtree: Creates a Stochastic mcnode Object using a Probability Tree

In mc2d: Tools for Two-Dimensional Monte-Carlo Simulations

Creates a Stochastic mcnode Object using a Probability Tree

Description

This function builds an ‘⁠mcnode⁠’ as a mixture ‘⁠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 an ‘⁠mcnode⁠’.
mcvalues	A named list of ‘⁠mcnode⁠’s, ‘⁠mcdata⁠’ functions or ‘⁠mcstoc⁠’ functions, or a combination of those objects. Each element should be or lead to a compatible ‘⁠mcnode⁠’ (see Details).
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 either:

• a vector of weights. They need not sum to one, but they should be nonnegative and not all zero. The length of this vector should equal the number of elements in the list ‘⁠mcvalues⁠’. Each elements of ‘⁠mcvalues⁠’ will appear in the final sample a random number of times with probability as specified by this vector.

• a ‘⁠"0 mcnode"⁠’ to build any type of node.

• a ‘⁠"V mcnode"⁠’ to build a ‘⁠"V mcnode"⁠’ or a ‘⁠"VU mcnode"⁠’.

• a ‘⁠"U mcnode"⁠’ to build a ‘⁠"U mcnode"⁠’ or a ‘⁠"VU mcnode"⁠’.

• a ‘⁠"VU mcnode"⁠’ to build a ‘⁠"VU mcnode"⁠’.

Each elements of ‘⁠mcvalues⁠’ may be either:

• a ‘⁠"0 mcnode"⁠’ to build any type of node.

• a ‘⁠"V mcnode"⁠’ to build a ‘⁠"V mcnode"⁠’ or a ‘⁠"VU mcnode"⁠’.

• a ‘⁠"U mcnode"⁠’ to build a ‘⁠"U mcnode"⁠’ or a ‘⁠"VU mcnode"⁠’.

• a ‘⁠"VU mcnode"⁠’ to build a ‘⁠"VU mcnode"⁠’.

Their 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.

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")

## The elements of mcvalues may be of various (but compatible) type
conc1 <- mcstoc(rnorm, type="V", mean=10, sd=2)
conc2 <- mcstoc(runif, type="U", min=-6, max=-5)
conc3 <- mcdata(0, type="0")
whichdist <- mcstoc(rempiricalD, type="VU", values=1:3, prob= c(.75, .20, .05))
mcprobtree(whichdist, list("1"=conc1, "2"=conc2, "3"=conc3), type="VU")

mc2d documentation built on July 26, 2023, 6:07 p.m.