Information Technology Reference
In-Depth Information
Value
In addition to the correlation monoplot described in Section 10.2.2, a list with the follow-
ing components is returned:
cor.X
, the correlation matrix of
X
;
adequacies
,theaxis
adequacies;
predictivities
, the axis predictivities; and
unit.cor.approx
,themea-
sure of how well each variable approximates the unit correlation of exact representations,
given algebraically by the square root of diag
(
V
2
JV
)
.
10.5.3 Function
MonoPlot.cor2
This function constructs the correlation monoplots described in Section 10.2.4 based on
the PCO of (10.4) with
R
as well as with
R
∗
R
. It takes the same arguments as
Mono-
Plot.cor
, but arguments
exp.factor
,
rotate.degrees
and
reflect
(see
PCAbipl
)
are also available.
Value
In addition to the two correlation monoplots described in Section 10.2.4, a list with the
following components is returned:
cor.X
, the correlation matrix of
X
;
adequacies.R
,
and
adequacies.R2
, the axis adequacies associated with
R
and
R
∗
R
, respectively.
10.5.4 Function
MonoPlot.coefvar
This is a function for constructing the coefficient of variation monoplot defined in
Section 10.2.3. Except for
scaled.mat
, it takes the same arguments as
MonoPlot.cov
.
In addition to the coefficient of variation monoplot (see Figure 10.7), it returns a list with
components:
cov.X
, the covariance matrix of
X
;
cor.X
, the correlation matrix of
X
;and
coefvar.vec
, the vector containing the coefficients of variation of all the variables.
10.5.5 Function
MonoPlot.skew
This is a function for constructing the hedron plots described in Section 10.3. It takes
only the following arguments:
A square matrix,
X
Optional argument for constructing a triangle on the hedron plot,
form.triangle1
Optional argument for constructing a second triangle on the
hedron plot,
form.triangle2
Optional arguments passed to the
points
function controlling
appearance of the plotted points,
...
In addition to the hedron plot (see Figure 10.11), it returns a list with components:
M
,
the symmetric
M
matrix defined in Section 10.4;
N
, the skew-symmetric
N
matrix defined
in Section 10.4;
K
,the
K
matrix defined in Section 10.4;
U
and
sigma
, the matrices
U
and
of the SVD (10.5).
