Ops.mcnode: 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 mcnode
Ops(e1, e2)

Value

The results as a mcnode object.

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.

Examples

Run this code

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