Multivariate Analysis: Canonical Discriminant Analysis |
The Plots Tab
You can use the Plots tab (Figure 29.10)
to create plots that graphically display
results of the analysis.
Figure 29.10: The Plots Tab
Creating a plot often adds one or more variables to the data table.
The following plots are available:
- Observed groups
-
creates a spine plot (a one-dimensional mosaic plot)
of the groups for the Y variable.
- Observed vs. Predicted groups
-
creates a mosaic plot of the groups for the Y variable versus the
group as classified by a discriminant function. Each observation is
placed in the group that minimizes the generalized squared
distance between the observation and the group mean.
- Classification fit plot
-
creates a plot that indicates how well each observation is classified
by the discriminant function. This plot is shown in
Figure 29.11. Observations that are close to two or
more group means are selected in the plot.
For each observation, PROC DISCRIM computes posterior probabilities
for membership in each group. Let be the maximum posterior
probability for the th observation.
The classification fit plot is a plot of versus .
Figure 29.11: A Classification Fit Plot
- Canonical score plot
-
creates a plot of the first two canonical variables.
(If there is only one canonical variable, then a histogram of that
variable is created instead.)
- Show group means
-
displays the mean of each group in the score plot.
- Add confidence ellipses for means
-
displays a confidence ellipse
for the mean of each group in the score plot.
- Confidence level
-
specifies the probability level for the confidence ellipse.
- Shade plot background by confidence level
-
specifies that the background of each scatter plot be shaded according
to a nested family of confidence ellipses.
- Add prediction ellipses
-
displays a prediction ellipse
for the mean of each group in the score
plot, assuming multivariate normality within each group.
- Prediction level
-
specifies the probability level for the prediction ellipse.
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