The CCDM Procedure
ODS Graphics
This section describes the use of ODS for creating graphics with the CCDM procedure.
Note: To create the plots, PROC CCDM prepares a plot data table that contains an estimate of the empirical distribution function (EDF) for a carefully selected subsample of the simulated aggregate loss sample and brings that table back to the client machine where your SAS session is running. You can control the size of the plot data table by specifying the NOBS= and NADJSEVTOPLOT= options. The larger the size of this table, the more accurate are the plots, but the more expensive it is to prepare and display the plots. So it is recommended that you request plots only when the full aggregate loss sample is not too large and that you do not specify large values for the NOBS= and NADJSEVTOPLOT= options.
ODS Graph Names
PROC CCDM assigns a name to each graph that it creates by using ODS. You can use these names to selectively refer to the graphs. The names are listed in Table 6.
Table 6: ODS Graphics Produced by PROC CCDM
| ODS Graph Name | Plot Description | PLOTS= Option |
|---|---|---|
| ConditionalDensityPlot | Conditional density plot | CONDITIONALDENSITY |
| DensityPlot | Probability density function plot | DENSITY |
| EDFPlot | Empirical distribution function plot | EDF |
Conditional Density Plot
The conditional density plot helps you visually analyze two or three regions of the compound distribution by displaying a density function estimate that is conditional on the values of the aggregate loss that fall in those regions. You can specify the region boundaries in terms of quantiles by using the LEFTQ= and RIGHTQ= suboptions of the PLOTS=CONDITIONALDENSITY option. This is especially useful if you want to see the distribution of aggregate loss values in the right- and left-tail regions.
If you specify m symbols in the ADJUSTEDSEVERITY= option and if you specify NADJSEVTOPLOT=k in the PLOTS= option, then separate sets of conditional density plots are displayed for the first l aggregate adjusted loss samples, where 
.
Probability Density Function Plot
The probability density function (PDF) plot shows the nonparametric estimates of the PDF of the aggregate loss distribution. This plot includes histogram and kernel density estimates.
If you specify m symbols in the ADJUSTEDSEVERITY= option and if you specify NADJSEVTOPLOT=k in the PLOTS= option, then separate density plots are displayed for the first l aggregate adjusted loss samples, where .
Empirical Distribution Function Plot
The empirical density function (EDF) plot shows the nonparametric estimate of the cumulative distribution function of the aggregate loss distribution. You can specify the ALPHA= suboption of the PLOTS=EDF option to request that the upper and lower confidence limits be plotted for each EDF estimate. By default, the confidence interval is not plotted.
If you specify m symbols in the ADJUSTEDSEVERITY= option and if you specify NADJSEVTOPLOT=k in the PLOTS= option, then separate EDF plots are displayed for the first l aggregate adjusted loss samples, where .