mcprobtree {mc2d} | R Documentation |
This function builds an mcnode as a mixture mcnode objects.
mcprobtree(mcswitch, mcvalues, type=c("V", "U", "VU", "0"), nsv=ndvar(), nsu=ndunc(), nvariates=1, outm="each", seed=NULL)
mcswitch |
A vector of probabilities/weights or an mcnode. |
mcvalues |
A named list of mcnodes, 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. |
mcswitch may be either:
Each elements of mcvalues may be either:
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.
An mcnode object.
Regis Pouillot
## 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")