For each data collector monitor it is possible to save the numerical data values that are extracted from a net during a simulation in a log file. The last line of the excerpt indicates that the value 1 was the 8th value collected, and it was collected after step 11 at model time 532.
Simulation performance reports provide an overview of the statistics that are calculated during one simulation for the Data collector monitors in a net.
Here is an example of a simulation performance report for a net that contains 6 data collector monitors. The net-specific “Simulation performance report” options can be used to select which statistics should be included in simulation performance reports. Note that if confidence intervals are included in simulation performance reports, then it is important to understand that the confidence interval for a particular data collector will not be accurate if the data values for the data collector are not independent and identically distributed (IID).
There may be a difference in the model time shown in the simulation performance report and the current model time shown in the index under the net overview. If Simulation stop criteria are met in a timed simulation at a time when there are no more enabled transitions, then CPN Tools will attempt to increase the model time to the next time at which a transition is enabled when Simulation feedback is updated. When Simulation replications are run and a net contains Data collector monitors, then some of the statistics that are calculated at the end of each simulation are used to calculate more reliable statistics that are based on data from the independent simulation replications.
The IID values for a number of different statistics are collected at the end of each simulation when running Simulation replications.
Note that these values can be found in the simulation performance reports for the corresponding three simulation performance reports. Replication performance reports contain statistics that are calculated for the data values that are found in replication log files. In the figure below, the row for avrg_iid in the section under Queue_Delay contains statistics for the values in the replication log file shown above.
The net-specific “Replication performance report” options can be used to select which statistics should be included in replication performance reports.
The confidence intervals that can be found in replication performance reports are also saved in plain text files.
Confidence interval files are saved in replication output directories, and are named confidenceintervalsX.txt where X is either 90, 95, or 99. It can be useful to compare confidence intervals for different levels for one set of simulation replications.


It can also be useful to run several different Simulation replications for different numbers of simulations to investigate the effects on both the estimate of the performance measure as well as the confidence intervals. When multiple simulation replications are run, scripts are generated for plotting data collector log files in the gnuplot program. Here is an example of a gnuplot script that will plot the data from three simulations for the Queue Length data collector monitor. An additional gnuplot script can be used to plot each of the data collector gnuplot scripts one after another. Here is an example of an automatically generated script that will load the gnuplot scripts that plot the log files for 6 different data collector monitors. For example, the animation below shows a two dimensional regression equation plotted with three different confidence intervals (90%, 95% and 99%). Robert Allison provided the code (proc gplot + annotate) to draw a dot plot with the confidence intervals.  This prompted follow up questions and discussion on whether such graphs (including Dot and BarCharts) can be created using SG procedures and GTL. The reason you cannot use the SAS 9.2 SGPLOT procedure to create the bar charts with the custom intervals is that the VBAR statement in proc SGPLOT computes its own intervals and does not allow overlay of other basic plot statements due to its special summarizing features.
See also "Creating bar charts with confidence intervals" for a discussion of which approach I prefer and why.
Yes, as long as the axis does not have a zero value, you can use an xaxis statement with type=log. Welcome to Graphically Speaking, a blog by Sanjay Matange focused on the usage of ODS Graphics for data visualization in SAS. The blog content appearing on this site does not necessarily represent the opinions of SAS.
The Logging option for a data collector monitor determines whether the data values will be saved in a log file.
The second line of the excerpt indicates that the value 0 was the first value collected, it was collected at step 0 and model time 0. The simulation performance report shown above was generated after the Fast forward tool was applied. This is what caused the difference between the model time in the simulation performance report and the current model time that was shown in the net overview after the simulation stopped. A number of different statistics are calculated for that data collector at the end of a simulation.


Since it is very likely that the values in the replication log files are IID, the confidence intervals in replication performance reports are more likely to be accurate than those in the simulation performance reports. The first column indicates the data collector and statistic for which the confidence interval has been calculated.
Below is a figure showing the 90%, 95%, and 99% confidence intervals for average queue delay based on data from 3 simulations. The script that is generated for a data collector monitor can be used to plot the log files from each of the n different simulations for the data collector. Neither the service provider nor the domain owner maintain any relationship with the advertisers. Since the value was collected at step 0, it must have been the value returned by the initialization function for the monitor.
A simulation performance report is saved in a simulation output directory immediately after the stop functions for monitors are invoked.
This means that the average of the data values at the end of the simulation is just one estimate of what the average for the data collector should be.
The values in a given replication log file are independent, and they are assumed to be identically distributed. In case of trademark issues please contact the domain owner directly (contact information can be found in whois). Running another simulation would most likely result in a different estimate of the average for the data collector in question.
By running multiple simulations, several IID estimates of a particular value, such as average marking size, or minimum list length can be collected.
The third column indicates the number of data values for which the average and confidence interval was calculated.



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