n x v data matrix; n observations and v variables. Rows of
Y represent observations, and columns represent variables.
Missing values (NaN's) and infinite values (Inf's) are
allowed, since observations (rows) with missing or infinite
values will automatically be excluded from the
computations.
Data Types: single|double
Specify optional comma-separated pairs of Name,Value arguments.
Name is the argument name and Value
is the corresponding value. Name must appear
inside single quotes (' ').
You can specify several name and value pair arguments in any order as
Name1,Value1,...,NameN,ValueN.
Example:
'madcoef',2
, 'rf',0.99
, 'robscale',2
, 'plots',2
, 'tag','new_tag'
, 'textlab',0
Coefficient which is used to scale MAD
coefficient to have a robust estimate of dispersion. The
default is 1.4815 so that 1.4815*MAD(N(0,1))=1.
Remark: if mad =median(y-median(y))=0 then the interquartile
range is used. If also the interquartile range is 0
than the MD (mean absolute deviation) is used. In
other words MD=mean(abs(y-mean(Y))
Example: 'madcoef',2
Data Types: double
0<rf<1.
The default value is 0.95 that is the outer contour in
presence of normality for each ellipse should leave
outside 5% of the values.
Example: 'rf',0.99
Data Types: double
It specifies the
statistical indexes to use to compute the dispersion of
each variable and the correlation among each pair of
variables.
robscale=1 (default): the program uses the median correlation
and the MAD as estimate of the dispersion of each variable;
robscale=2: the correlation coefficient among ranks is used
(Spearman's rho) and the MAD as estimate of the dispersion
of each variable;
robscale=3: the correlation coefficient is based on Kendall's tau b
and the MAD as estimate of the dispersion of each
variable;
robscale=4: tetracoric correlation coefficient is used and the MAD
as estimate of the dispersion of each variable;
otherwise the correlation and the dispersion of the variables are
computed using the traditional (non robust) formulae
around the univariate medians.
Example: 'robscale',2
Data Types: double
It specifies whether it is
necessary to produce a plot
with univariate standardized boxplots on the
main diagonal and bivariate confidence ellipses out of
the main diagonal. If plots is equal to 1 a plot
which contains univariate standardized boxplots on the
main diagonal and bivariate confidence ellipses out of
the main diagonal is produced on the screen. If plots is
<> 1 no plot is produced. As default no plot is
produced.
Example: 'plots',2
Data Types: double
It identifies the handle of the plot which
is about to be created. The default is to use tag
'pl_unibiv'. Notice that if the program finds a plot which
has a tag equal to the one specified by the user, then
the output of the new plot overwrites the existing one
in the same window else a new window is created.
Example: 'tag','new_tag'
Data Types: char
Scalar which controls the labels in
the plots. If textlab=1 and
plots=1 the labels associated
to the units which are univariate outliers or which are
outside the confidence levels of the contours are
displayed on the screen.
Example: 'textlab',0
Data Types: double
unibiv with optional arguments.
