Event Takeover Values (ETV) measure the impact of each individual in the population dynamics of evolutionary algorithms (EA). Previous studies argue that ETV distribution of panmictic EAs fit power laws with exponent between 2.2 and 2.5 and that this property is insensitive to fitness landscapes and design choices of the EAs. One exception is cellular EAs, for which there are deviations of the power law for large values. In this paper, ETVs for structured and panmictic EAs with different population size and mutation probability on several fitness landscapes were computed. Although the ETVs distribution of pamictic EAs is heavy-tailed, the log-log plot of the complementary cumulative distributed function shows no linearity. Furthermore, Vuong's tests on the distributions generated by several instances of the problems conclude that power law models cannot be favored over log-normal models. On the other hand, the tests confirm that cEAs impose significant deviations to the distribution tail.
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