Randomization tests for initialization bias in simulation output

A new approach for detecting initialization bias in the mean of a simulation output series is presented. The problem is cast in a hypothesis-testing framework using randomization (permutation) tests. The approach is extremely flexible in that it enables the use of a wide variety of test statistics. Moreover, no assumptions are needed concerning the distribution of the sample of observations. The test is computationally intensive; however, the required computing power does not exceed the capabilities of a personal computer.