Editing Network traffic simulation (section)

==Statistical issues in simulation modelling==

===Input data===

Simulation models are generated from a set of data taken from a stochastic system. It is necessary to check that the data is statistically valid by fitting a statistical distribution and then testing the significance of such a fit. Further, as with any modelling process, the input data’s accuracy must be checked and any outliers must be removed.<ref name="flood" />

===Output data===

When a simulation has been completed, the data needs to be analysed. The simulation's output data will only produce a likely ''estimate'' of real-world events. Methods to increase the accuracy of output data include: repeatedly performing simulations and comparing results, dividing events into batches and processing them individually, and checking that the results of simulations conducted in adjacent time periods “connect” to produce a coherent holistic view of the system.<ref name="flood" /><ref name="akimaru">Akimaru H., Kawashima K., ''Teletraffic – Theory and Applications'', Springer-Verlag London, 2nd Edition, 1999, pg 6</ref>

===Random numbers===

As most systems involve stochastic processes, simulations frequently make use of random number generators to create input data which approximates the random nature of real-world events. Computer generated [random numbers] are usually not random in the strictest sense, as they are calculated using a set of equations. Such numbers are known as pseudo-random numbers. When making use of pseudo-random numbers the analyst must make certain that the true randomness of the numbers is checked. If the numbers are found not to behave in a sufficiently random fashion, another generation technique must be found. Random numbers for the simulation are created by a [[random number generator]].