| Ops.mcnode {mc2d} | R Documentation |
Operations on mcnode Objects
Description
This function alters the way operations are performed on ‘mcnode’ objects for a better consistency of the theory.
Usage
## S3 method for class 'mcnode'
Ops(e1, e2)
Arguments
e1 |
An ‘mcnode’ object, a vector or an array. |
e2 |
An optional ‘mcnode’ object, a vector or a matrix with at least one of both objects as an ‘mcnode’. |
Details
This method will be used for any of the Group Ops
functions.
The rules are as following (illustrated with a ‘+’ function and ignoring the ‘nvariates’ dimension):
-
‘0 + 0 = 0’;
-
‘0 + V = V’: classical recycling of the scalar;
-
‘0 + U = U’: classical recycling of the scalar;
-
‘0 + VU = VU’: classical recycling of the scalar;
-
‘V + V = V’: if both of the same ‘(nsv)’ dimension;
-
‘V + U = VU’: the ‘U’ object will be recycled "by row". The ‘V’ object will be recycled classically "by column";
-
‘V + VU = VU’: if the dimension of the ‘V’ is ‘(nsv)’ and the dimension of the ‘VU’ is ‘(nsv x nsu)’. The ‘V’ object will be recycled classically "by column";
-
‘U + U = U’: if both of the same ‘(nsu)’ dimension;
-
‘U + VU = VU’: if the dimension of the ‘U’ is ‘(nsu)’ and the dimension of the ‘VU’ is ‘(nsv x nsu)’. The ‘U’ object will be recycled "by row";
-
‘VU + VU = VU’: if the dimension of the ‘VU’ nodes is ‘(nsu x nsv)’;
A vector or an array may be combined with an ‘mcnode’ of size
‘(nsv x nsu)’ if an ‘mcnode’ of this dimension may be built
from this vector/array using the ‘mcdata’ function. See
mcdata for the rules.
The ‘outm’ attribute is transferred as following: ‘each +
each = each’; ‘none + other = other’; ‘other1 + other2 =
other1’. The ‘outm’ attribute of the resulting node may be
changed using the outm function.
For multivariate nodes, a recycling on the ‘nvariates’ dimension is done if a ‘(nsu x nsv x nvariates)’ node is combined with a ‘(nsu x nsv x 1)’ node.
Value
The results as a ‘mcnode’ object.
See Also
Examples
oldvar <- ndvar()
oldunc <- ndunc()
ndvar(30)
ndunc(20)
## Given
x0 <- mcdata(3, type="0")
xV <- mcdata(1:ndvar(), type="V")
xU <- mcdata(1:ndunc(), type="U")
xVU <- mcdata(1:(ndunc()*ndvar()), type="VU")
x0M <- mcdata(c(5, 10), type="0", nvariates=2)
xVM <- mcdata(1:(2*ndvar()), type="V", nvariates=2)
xUM <- mcdata(1:(2*ndunc()), type="U", nvariates=2)
xVUM <- mcdata(1:(2*(ndunc()*ndvar())), type="VU", nvariates=2)
## All possible combinations
## "0"
-x0
x0 + 3
## "V"
-xV
3 + xV
xV * (1:ndvar())
xV * x0
xV - xV
## "U"
-xU
xU + 3
(1:ndunc()) * xU
xU * x0
xU - xU
## Watch out the resulting type
xV + xU
xU + xV
## "VU"
-xVU
3 + xVU
(1:(ndunc()*ndvar())) * xVU
xVU + xV
x0 + xVU
xU + xVU
xVU - xVU
## Some Multivariates
x0M+3
xVM * (1:ndvar())
xVM - xV
xUM - xU
xVUM - xU