network
allows to infer large-scale association networks
between the $X$ and $Y$ datasets in rcc
or spls
. The output is a graph where
each $X$- and $Y$-variable corresponds to a node and the edges
included in the graph portray associations between them.In rcc
, to identify $X$-$Y$ pairs showing relevant associations, network
calculate a
similarity measure between $X$ and $Y$ variables in a pair-wise manner: the
scalar product value between every pairs of vectors in dimension length(comp)
representing
the variables $X$ and $Y$ on the axis defined by $Z_i$ with $i$ in comp
,
where $Z_i$ is the equiangular vector between the $i$-th $X$ and $Y$ canonical variate.
In spls
, if object$mode
is regression
, the similarity measure between $X$ and
$Y$ variables is given by the scalar product value between every pairs of vectors in dimension
length(comp)
representing the variables $X$ and $Y$ on the axis defined by $U_i$ with
$i$ in comp
, where $U_i$ is the $i$-th $X$ variate. If object$mode
is
canonical
then $X$ and $Y$ are represented on the axis defined by $U_i$ and $V_i$
respectively.
Variable pairs with a high similarity measure (in absolute value) are considered as relevant.
By changing the threshold, one can tune the relevance of the associations to include or
exclude relationships in the network.
interactive=TRUE
open two device, one for association network, one for scrollbar,
and define an interactive process: by clicking either at each end
(`$-$' or `$+$') of the scrollbar or
at middle portion of this. The position of the slider indicate which is the `threshold' value
associated to the display network.
The interactive process is terminated by clicking the second button and selecting `Stop'
from the menu, or from the `Stop' menu on the graphics window.
The color.node
is a vector of length two,
of any of the three kind of R
colors, i.e., either a color name
(an element of colors()
), a hexadecimal string of the form "#rrggbb"
,
or an integer i
meaning palette()[i]
. color.node[1]
and
color.node[2]
give the color for filled nodes of the $X$- and $Y$-variables
respectively. Defaults to c("white", "white")
.
color.edge
give the color to edges with colors corresponding to the values in
mat
. Defaults to c("blue", "red")
for low and high weight respectively.
shape.node[1]
and shape.node[2]
provide the shape of the nodes associate
to $X$- and $Y$-variables respectively. Current acceptable values are
"circle"
and "rectangle"
. Defaults to c("circle", "rectangle")
.
lty.edge[1]
and lty.egde[2]
give the line type to edges with positive
and negative weight respectively. Can be one of "solid"
, "dashed"
,
"dotted"
, "dotdash"
, "longdash"
and "twodash"
. Defaults
to c("solid", "solid")
.
lwd.edge[1]
and lwd.edge[2]
provide the line width to edges with positive
and negative weight respectively. This attribute is of type double with
a default of c(1, 1)
.