mcnode {mc2d} | R Documentation |
Creates a mcnode object from a vector, an array or a mcnode.
mcdata(data, type=c("V", "U", "VU", "0"), nsv=ndvar(), nsu=ndunc(), nvariates=1, outm="each") mcdatanocontrol(data, type=c("V", "U", "VU", "0"), nsv=ndvar(), nsu=ndunc(), nvariates=1, outm="each")
data |
The numeric/logical vector/matrix/array of data or the mcnode object. |
type |
The type of node to be built. By default, a "V" node. |
nsv |
The variability dimension (type="V" or
type="VU") of the node. By default: the current value in
mc.control |
nsu |
The uncertainty dimension (type="U" or
type="VU") of the node. By default: the current value in
mc.control |
nvariates |
The number of variates. By default: 1 |
outm |
The output of the mcnode for multivariates nodes.
May be "each" (default) if output should be provided for each
variates considered independently, "none" for no output or a vector
of name of function(s) (as a character string) that will be applied
on the variates dimension before any output (ex: "mean",
"median", c("min", "max")). The function should have no
other arguments and send one value per vector of values (ex. do not
use "range"). Note that the outm attribute may be
changed at any time using the outm function. |
A mcnode object is the basic element of a mc
object. It is an array of dimension (nsv x nsu x nvariates).
Four types of mcnode exists:
Multivariate nodes (i.e. nvariates != 1) should be used for
multivariate distributions implemented in mc2d
(rmultinomial
, rmultinormal
,
rempiricalD
and rdirichlet
).
For security, recycling rules are limited to fill the array using data. The general rules is that recycling is only permitted to fill a dimension from 1 to the final size of the dimension.
If the final dimension of the node is (nsv x nsu x nvariates) (with nsv = 1 and nsu = 1 for "0" nodes, nsu = 1 for "V" nodes and nsv = 1 for "U" nodes), mcdata accepts :
An mcnode object.
Regis Pouillot
mcstoc
to build a stochastic mcnode object,
mcprobtree
to build a stochastic node fro a probability
tree.
Ops.mcnode
for operations on mcnode objects.
mc
to build a Monte-Carlo object.
Informations about an mcnode: is.mcnode
,
dimmcnode
, typemcnode
.
To build a correlation structure between mcnode:
cornode
.
To study mcnode objects: print.mcnode
,
summary.mcnode
, plot.mcnode
,
converg
, hist.mcnode
To modify mcnode objects: NA.mcnode
oldvar <- ndvar() oldunc <- ndunc() ndvar(3) ndunc(5) (x0 <- mcdata(100, type="0")) mcdata(matrix(100), type="0") (xV <- mcdata(1:ndvar(), type="V")) mcdata(matrix(1:ndvar(), ncol=1), type="V") (xU <- mcdata(10*1:ndunc(), type="U")) mcdata(matrix(10*1:ndunc(), nrow=1), type="U") (xVU <- mcdata(1:(ndvar()*ndunc()), type="VU")) mcdata(matrix(1:(ndvar()*ndunc()), ncol=5, nrow=3), type="VU") ##Do not use ## Not run: mcdata(matrix(1:5, nrow=1), type="VU") ## End(Not run) ##use instead mcdata(mcdata(matrix(1:ndunc(), nrow=1), type="U"), "VU") ##or mcdata(matrix(1:ndunc(), nrow=1), type="U") + mcdata(0, "VU") mcdata(x0, type="0") mcdata(x0, type="V") mcdata(xV, type="V") mcdata(x0, type="U") mcdata(xU, type="U") mcdata(x0, type="VU") mcdata(xU, type="VU") mcdata(xV, type="VU") ##Multivariates (x0M <- mcdata(1:2, type="0", nvariates=2)) mcdata(1, type="0", nvariates=2) (xVM <- mcdata(1:(2*ndvar()), type="V", nvariates=2)) mcdata(1:ndvar(), type="V", nvariates=2) mcdata(array(1:(2*ndvar()), dim=c(3, 1, 2)), type="V", nvariates=2) mcdata(1, type="V", nvariates=2) mcdata(x0, type="V", nvariates=2) mcdata(x0M, type="V", nvariates=2) mcdata(xV, type="V", nvariates=2) mcdata(xVM, type="V", nvariates=2) (xUM <- mcdata(10*(1:(2*ndunc())), type="U", nvariates=2)) mcdata(array(10*(1:(2*ndunc())), dim=c(1, 5, 2)), type="U", nvariates=2) mcdata(1, type="U", nvariates=2) mcdata(x0, type="U", nvariates=2) mcdata(x0M, type="U", nvariates=2) mcdata(xU, type="U", nvariates=2) mcdata(xUM, type="U", nvariates=2) (xVUM <- mcdata(1:(ndvar()*ndunc()), type="VU", nvariates=2)) mcdata(array(1:(ndvar()*ndunc()), dim=c(3, 5, 2)), type="VU", nvariates=2) mcdata(1, type="VU", nvariates=2) mcdata(x0, type="VU", nvariates=2) mcdata(x0M, type="VU", nvariates=2) mcdata(xV, type="VU", nvariates=2) mcdata(xVM, type="VU", nvariates=2) mcdata(xU, type="VU", nvariates=2) mcdata(xUM, type="VU", nvariates=2) mcdata(xVU, type="VU", nvariates=2) mcdata(xVUM, type="VU", nvariates=2) ndvar(oldvar) ndunc(oldunc)